Seminar / Colloquium

EE380 Computer Systems Colloquium presents "How Behavior Spreads"

Topic: 
How Behavior Spreads
Abstract / Description: 

New social movements, technologies, and public-health initiatives often struggle to take off, yet many diseases disperse rapidly without issue. Can the lessons learned from the viral diffusion of diseases be used to improve the spread of beneficial behaviors and innovations? In this talk, I discuss several new breakthroughs in the science of network diffusion, and how these advances have improved our understanding of how changes in societal behavior--in voting, health, technology, and finance--occur, and the ways social networks can be used to influence how they propagate. The findings show that the same conditions accelerating the viral expansion of an epidemic unexpectedly inhibit the spread of behaviors. I show how many of the most well-known, intuitive ideas about how social networks function have in fact been responsible for causing past diffusion efforts to fail. I present new findings and new network methods that have been used to enable social change efforts to succeed much more effectively.

For futher reading please consult:

 

Date and Time: 
Wednesday, November 14, 2018 - 4:30pm
Venue: 
Gates B03

ISL Colloquium presents Estimating the Information Flow in Deep Neural Networks

Topic: 
Estimating the Information Flow in Deep Neural Networks
Abstract / Description: 

This talk will discuss the flow of information and the evolution of internal representations during deep neural network (DNN) training, aiming to demystify the compression aspect of the information bottleneck theory. The theory suggests that DNN training comprises a rapid fitting phase followed by a slower compression phase, in which the mutual information I(X;T) between the input X and internal representations T decreases. Several papers observe compression of estimated mutual information on different DNN models, but the true I(X;T) over these networks is provably either constant (discrete X) or infinite (continuous X). We will explain this discrepancy between theory and experiments, and explain what was actually measured by these past works.

To this end, an auxiliary (noisy) DNN framework will be introduced, in which I(X;T) is a meaningful quantity that depends on the network's parameters. We will show that this noisy framework is a good proxy for the original (deterministic) system both in terms of performance and the learned representations. To accurately track I(X;T) over noisy DNNs, a differential entropy estimator tailor to exploit the DNN's layered structure will be developed and theoretical guarantees on the associated minimax risk will be provided. Using this estimator along with a certain analogy to an information-theoretic communication problem, we will elucidate the geometric mechanism that drives compression of I(X;T) in noisy DNNs. Based on these findings, we will circle back to deterministic networks and explain what the past observations of compression were in fact showing. Future research directions inspired by this study aiming to facilitate a comprehensive information-theoretic understanding of deep learning will also be discussed.

Date and Time: 
Friday, November 9, 2018 - 1:15pm
Venue: 
Packard 202

Power Magnetics: Addressing the Bottleneck in Energy Systems

Topic: 
Power Magnetics: Addressing the Bottleneck in Energy Systems
Abstract / Description: 

Power conversion is a hidden hindrance to many of our most exciting and necessary developing technologies, including renewable energy, robotics, electrified transportation, and power-hungry artificial intelligence. At the same time, a new power technology landscape has emerged which has shifted the performance bottleneck to magnetic components. Indeed, inductors and transformers now routinely dominate both the size and losses in power converters, and converters in turn frequently limit the performance of the overall application. Improvements in power magnetics thus have a direct path to societal impact.

To relieve the magnetics bottleneck, we must improve materials, structures, and circuit architectures to take advantage of advanced components. To make an impact, we also need to enable industry to apply these important research conclusions. This seminar will present recent discoveries in high- performance magnetic materials, very low loss high-frequency inductor structures, and recent efforts to apply these advancements to current industrial applications. In addition, we will discuss how we are transforming these advancements from laboratory proofs-of-concept to profitable realities, with impact on systems at orders-of-magnitude different power levels.

 

Date and Time: 
Tuesday, November 6, 2018 - 3:00pm
Venue: 
Lathrop Library, Bishop Auditorium

ISL Colloquium presents When do neural networks have bad local minima, and when not?

Topic: 
When do neural networks have bad local minima, and when not?
Abstract / Description: 

To explain the recent success of neural networks, researchers have conjectured that all local minima are global minima despite the non-convexity of the problem. Is this really true? Is this just hand-wavy intuition that is roughly true in special cases or can be a rigorous result in a broad setting?

In this talk, instead of explaining "why neural-nets are good", we try to understand "when neural-nets are good, and when not" --with a restricted definition of "good" by "every local-min is global-min". We focus on the binary classification problem and discuss how architecture and data affect the landscape. On the positive side, we prove that no bad local minima exist under reasonable assumptions on the neuron types, the neural-net structure, the loss function, and the dataset. On the negative side, we provide dozens of counterexamples that show the necessity of most assumptions.

Our approach can be viewed as a game of "local-min attack" and "defense". An attacker tries to construct examples that bad local minima exist, and the defender modifies the setting to eliminate bad local minima. For instance, the attacker constructs bad local minima for 1-hidden-layer ReLU network with linearly separable data, then the defender proves that smooth versions of ReLU eliminate them. At last, we present a strong defense consisting of a special neuron and a special regularizer that can eliminate bad local minima for a deep neural-net in the realizable case.

Joint work with Shiyu Liang, Yixuan Li, Jason Lee and R. Srikant.

Date and Time: 
Thursday, November 8, 2018 - 4:15pm
Venue: 
Packard 101

SystemX Seminar presents Beyond the hardware: Why you should launch a brand, not just a product

Topic: 
Beyond the hardware: Why you should launch a brand, not just a product
Abstract / Description: 

In the race to launch a product, the concept of "brand" is often an afterthought. Truth is, building a brand is basic to product survival. Good branding communicates quality, credibility and value. It outlives product cycles and inspires customer loyalty. So, how is an effective brand crafted? Diving into a collection of case studies, this talk will explore why design is essential for thinking beyond the hardware to create a brand that fosters an emotional connection between person and product.

Date and Time: 
Thursday, November 8, 2018 - 4:30pm
Venue: 
Huang 018

SystemX Seminar BONUS LECTURE: New Mysteries vs Advanced Technology in Radio Astronomy

Topic: 
New Mysteries vs Advanced Technology in Radio Astronomy
Abstract / Description: 

1. New Mysteries

  • Fast Radio Bursts, FRB's – 1ms pulses, non‐recurring, which strike the earth at a rate of 5000 per day, and are of unknown orgin – more about this
  • Gravitational Waves – detected by LIGO but very coarse directions; need radio or optical observations to locate and understand the orgins
  • Recent Nature paper on 78 MHz dip in cosmic background ‐ needs confirmation and theoretical explanation

2. Transformational Radio Telescopes – The traditional need for large collecting area and sharp beamwidths needs to be supplemented by telescopes which can find transients from unknown directions in the sky,

  • Current example, all the sky, all the time – The Caltech long wavelength array
  • DSA, an array to locate and understand the orgins of FRB's
  • Next generation affordable array, 2000 x 5m telescopes.

3. Advanced RF Technology for Radio Astronomy and Quantum Computing

  • Ultra low noise without cryogenics – 1.4 GHz LNA with 12K noise
  • Development of wireless, solar powered, radio telescopes
  • LNA requirements for quantum computing – effects of self heating
Date and Time: 
Wednesday, November 7, 2018 - 2:00pm
Venue: 
Packard 202

IT-Forum presents Estimating the Information Flow in Deep Neural Networks

Topic: 
Estimating the Information Flow in Deep Neural Networks
Abstract / Description: 

This talk will discuss the flow of information and the evolution of internal representations during deep neural network (DNN) training, aiming to demystify the compression aspect of the information bottleneck theory. The theory suggests that DNN training comprises a rapid fitting phase followed by a slower compression phase, in which the mutual information I(X;T) between the input X and internal representations T decreases. Several papers observe compression of estimated mutual information on different DNN models, but the true I(X;T) over these networks is provably either constant (discrete X) or infinite (continuous X). We will explain this discrepancy between theory and experiments, and explain what was actually measured by these past works.

To this end, an auxiliary (noisy) DNN framework will be introduced, in which I(X;T) is a meaningful quantity that depends on the network's parameters. We will show that this noisy framework is a good proxy for the original (deterministic) system both in terms of performance and the learned representations. To accurately track I(X;T) over noisy DNNs, a differential entropy estimator tailor to exploit the DNN's layered structure will be developed and theoretical guarantees on the associated minimax risk will be provided. Using this estimator along with a certain analogy to an information-theoretic communication problem, we will elucidate the geometric mechanism that drives compression of I(X;T) in noisy DNNs. Based on these findings, we will circle back to deterministic networks and explain what the past observations of compression were in fact showing. Future research directions inspired by this study aiming to facilitate a comprehensive information-theoretic understanding of deep learning will also be discussed.

Date and Time: 
Wednesday, October 31, 2018 - 1:15pm
Venue: 
Packard 202

EE380 Computer Systems Colloquium presents "Partisan Gerrymandering and the Supreme Court: The Role of Social Science"

Topic: 
Partisan Gerrymandering and the Supreme Court: The Role of Social Science
Abstract / Description: 

***The talk for October 31, 2018 is drawn from our back list of videos and will not be a live presentation. This talk was originally given November 1, 2017. ***
We have been planning to have a speaker for this slot to address the issues of elections in a technological state. Despite many discussions and invitations, we have been unable to find anyone willing to take on speak about the current juncture of politics, technology, and economics.

The U.S. Supreme Court is considering a case this term, Gill v Whitford, that might lead to the first constitutional constraints on partisanship in redistricting. Eric McGhee is the inventor of the efficiency gap, a measure of gerrymandering that the court is considering in the case. He will describe the case's legal background, discuss some of the metrics that have been proposed for measuring gerrymandering, and reflect on the role of social science in the litigation.

Related NPR Science Friday Talk (Nov 3):

Does Math Have A Place In The Courtroom. Audio is 17 minutes.
So is it possible that these Ivy League-educated Supreme Court justices really don't understand the math of this case? Oliver Roeder, senior writer for FiveThirtyEight joins Ira to discuss whether the Supreme Court is allergic to math, and what that means for future cases. And Moon Duchin, associate professor of mathematics at Tufts University, returns to discuss the best math to use for rooting out gerrymandering.

Date and Time: 
Wednesday, October 31, 2018 - 4:30pm
Venue: 
Gates B03

AP483, Ginzton Lab, & AMO Seminar Series presents Impact of Structural Correlation and Monomer Heterogeneity in the Phase Behavior of Soft Materials and Chromosomal DNA

Topic: 
Impact of Structural Correlation and Monomer Heterogeneity in the Phase Behavior of Soft Materials and Chromosomal DNA
Abstract / Description: 

Polymer self-assembly plays a critical role in a range of soft-material applications and in the organization of chromosomal DNA in living cells. In many cases, the polymer chains are composed of incompatible monomers that are not regularly arranged along the chains. The resulting phase segregation exhibits considerable heterogeneity in the microstructures, and the size scale of these morphologies can be comparable to the statistical correlation that arises from the molecular rigidity of the polymer chains. To establish a predictive understanding of these effects, molecular models must retain sufficient detail to capture molecular elasticity and sequence heterogeneity. This talk highlights efforts to capture these effects using analytical theory and computational modeling. First, we demonstrate the impact of structural rigidity on the phase segregation of copolymer chain in the melt phase, resulting in non-universal phase phenomena due to the interplay of concentration fluctuations and structural correlation. We then demonstrate how these effects impact the phase behavior in statistical random copolymers and in heterogeneous copolymers based on chromosomal DNA properties. With these results, we demonstrate that the spatial segregation of DNA in living cells can be predicted using a heterogeneous copolymer model of microphase segregation.

Date and Time: 
Monday, November 5, 2018 - 4:15pm
Venue: 
Spilker 232

ISL Colloquium presents Taming the Devil of Gradient-based Optimization Methods with the Angel of Differential Equations

Topic: 
Taming the Devil of Gradient-based Optimization Methods with the Angel of Differential Equations
Abstract / Description: 

In this talk, we use ordinary differential equations to model, analyze, and interpret gradient-based optimization methods. In the first part of the talk, we derive a second-order ODE that is the limit of Nesterov's accelerated gradient method for non-strongly objectives (NAG-C). The continuous-time ODE is shown to allow for a better understanding of NAG-C and, as a byproduct, we obtain a family of accelerated methods with similar convergence rates. In the second part, we begin by recognizing that existing ODEs in the literature are inadequate to distinguish between two fundamentally different methods, Nesterov's accelerated gradient method for strongly convex functions (NAG-SC) and Polyak's heavy-ball method. In response, we derive high-resolution ODEs as more accurate surrogates for the three aforementioned methods. These novel ODEs can be integrated into a general framework that allows for a fine-grained analysis of the discrete optimization algorithms through translating properties of the amenable ODEs into those of their discrete counterparts. As the first application of this framework, we identify the effect of a term referred to as 'gradient correction' in NAG-SC but not in the heavy-ball method, shedding insight into why the former achieves acceleration while the latter does not. Moreover, in this high-resolution ODE framework, NAG-C is shown to boost the squared gradient norm minimization at the inverse cubic rate, which is the sharpest known rate concerning NAG-C itself. Finally, by modifying the high-resolution ODE of NAG-C, we obtain a family of new optimization methods that are shown to maintain the accelerated convergence rates as NAG-C for smooth convex functions. This is based on joint work with Stephen Boyd, Emmanuel Candes, Simon Du, Michael Jordan, and Bin Shi.

Date and Time: 
Thursday, November 1, 2018 - 4:15pm
Venue: 
Packard 101

Pages

Applied Physics / Physics Colloquium

AP483, Ginzton Lab, & AMO Seminar Series presents Impact of Structural Correlation and Monomer Heterogeneity in the Phase Behavior of Soft Materials and Chromosomal DNA

Topic: 
Impact of Structural Correlation and Monomer Heterogeneity in the Phase Behavior of Soft Materials and Chromosomal DNA
Abstract / Description: 

Polymer self-assembly plays a critical role in a range of soft-material applications and in the organization of chromosomal DNA in living cells. In many cases, the polymer chains are composed of incompatible monomers that are not regularly arranged along the chains. The resulting phase segregation exhibits considerable heterogeneity in the microstructures, and the size scale of these morphologies can be comparable to the statistical correlation that arises from the molecular rigidity of the polymer chains. To establish a predictive understanding of these effects, molecular models must retain sufficient detail to capture molecular elasticity and sequence heterogeneity. This talk highlights efforts to capture these effects using analytical theory and computational modeling. First, we demonstrate the impact of structural rigidity on the phase segregation of copolymer chain in the melt phase, resulting in non-universal phase phenomena due to the interplay of concentration fluctuations and structural correlation. We then demonstrate how these effects impact the phase behavior in statistical random copolymers and in heterogeneous copolymers based on chromosomal DNA properties. With these results, we demonstrate that the spatial segregation of DNA in living cells can be predicted using a heterogeneous copolymer model of microphase segregation.

Date and Time: 
Monday, November 5, 2018 - 4:15pm
Venue: 
Spilker 232

Applied Physics/Physics Colloquium: Quantum mechanical bounds on transport and chaos

Topic: 
Quantum mechanical bounds on transport and chaos
Abstract / Description: 

Transport in strongly quantum systems is challenging to understand. I will describe a recently obtained bound on transport in terms of a characteristic quantum velocity (the Lieb-Robinson velocity) and the local thermalization time. This bound sheds some light on experiments in both condensed matter systems and ultracold atomic gases. At finite temperatures, a more powerful velocity is the so-called butterfly velocity, that is intimately related to quantum chaos. This velocity is still poorly understood; I will present some forthcoming results that constrain the temperature dependence of the butterfly velocity in terms of the underlying quantum scrambling of the system.

Date and Time: 
Monday, October 8, 2018 - 4:15pm
Venue: 
Spilker 232

Applied Physics/Physics Colloquium presents d = 4 N = 2 Field Theory and Physical Mathematics

Topic: 
d = 4 N = 2 Field Theory and Physical Mathematics
Abstract / Description: 

d = 4 N = 2 Field Theory and Physical Mathematics

I will explain the meaning of the two phrases in the title. Much of the talk will be a review of the renowned Seiberg-Witten formulation of the low-energy physics of certain four dimensional supersymmetric interacting quantum field theories. In the latter part of the talk I will briefly describe some of the significant progress that has been made in solving for the so-called BPS sector of the Hilbert space of these theories. Investigations into these physical questions have had a nontrivial impact on mathematics.


 

Aut. Qtr. Colloq. committee: R. Blandford (Chair), A. Kapitulnik, R. Laughlin, L. Senatore
Location: Hewlett Teaching Center, Rm. 200

Date and Time: 
Tuesday, November 27, 2018 - 4:30pm
Venue: 
Hewlett 200

Applied Physics/Physics Colloquium presents Searching for Dark Sectors Under our Noses

Topic: 
Searching for Dark Sectors Under our Noses: Surprising Opportunities at Familiar Mass Scales
Abstract / Description: 

Dark matter is as mysterious as it is ubiquitous. Cosmological evidence raises more questions than it answers about the origin and nature of the most abundant kind of matter in the Universe. Terrestrial experiments searching for answers have focused mainly on the possibility that the constituent of dark matter is a new particle near the Higgs boson mass scale - at the upper limit of the energy ranges ever explored in the laboratory. But recent years have seen a growing interest in the possibility that dark matter is made of particles in a far more pedestrian mass range, comparable to protons or electrons or somewhere in between. Such light dark matter particles could be hiding under our noses, kinematically easy to produce in the laboratory but difficult to detect because they are only produced rarely, through feeble interactions. I will discuss the theoretical underpinnings of sub-GeV dark matter, and the intriguing possibility that dark matter could be our first window into a "dark sector" with new particles and interactions. I will also discuss prospects for new small-scale experiments to explore these ideas, and the exciting prospect that the most strongly motivated parameter space is within reach of next-generation experiments.


 

Aut. Qtr. Colloq. committee: R. Blandford (Chair), A. Kapitulnik, R. Laughlin, L. Senatore
Location: Hewlett Teaching Center, Rm. 200

Date and Time: 
Tuesday, November 13, 2018 - 4:30pm
Venue: 
Hewlett 200

Applied Physics/Physics Colloquium presents High Energy Density Physics – Theory and Experiment in the Realm of the Superlasers

Topic: 
High Energy Density Physics – Theory and Experiment in the Realm of the Superlasers
Abstract / Description: 

High energy density physics may be loosely defined as the study and application of matter and energy above one megabar in pressure – roughly 1 eV/atomic ion at solid density. This regime is characterized by strong ionization, the ubiquity of shocks, fast hydrodynamic instabilities, and the importance of radiation transport in the energy balance of the medium. The microphysics of this regime necessarily deals with the combinatorial complexity of multiply excited atomic ions interacting with radiation. Beyond normal terrestrial experience until recently, the high energy density regime is now the subject of concerted laser and pulsed power experimentation. Examples of applications include stellar astrophysics and inertial confinement fusion. In this colloquium, I will discuss recent theoretical and experimental developments in three significant areas that exemplify the challenges and impact of this physical regime: radiation transfer in local thermal equilibrium and more generally non-local equilibrium, and dynamical viscosity.


 

Aut. Qtr. Colloq. committee: R. Blandford (Chair), A. Kapitulnik, R. Laughlin, L. Senatore
Location: Hewlett Teaching Center, Rm. 200

Date and Time: 
Tuesday, November 6, 2018 - 4:30pm
Venue: 
Hewlett 200

Applied Physics/Physics Colloquium presents The Dynamic Local Universe

Topic: 
The Dynamic Local Universe
Abstract / Description: 

New three-dimensional measurements of the positions and velocities of stars, in particular from the Gaia observatory, have provided unprecedented information on the dynamics of the Milky Way and nearby galaxies. Stellar streams and phase-space structures have been characterized, pointing towards an active recent accretion history by the Milky Way. In this talk, I will discuss how these observations inform hierarchical structure formation, the Milky Way, the Local Group of galaxies, and the nature of dark matter. I will discuss what we can expect from future Gaia data and future astrometric observations.


 

Aut. Qtr. Colloq. committee: R. Blandford (Chair), A. Kapitulnik, R. Laughlin, L. Senatore
Location: Hewlett Teaching Center, Rm. 200

Date and Time: 
Tuesday, October 30, 2018 - 4:30pm
Venue: 
Hewlett 200

Applied Physics/Physics Colloquium: Visiting Newton's Atelier before the Principia, 1679-1684

Topic: 
Visiting Newton's Atelier before the Principia, 1679-1684
Abstract / Description: 

Newton's Principia ignited the Scientific Revolution, but the work-sheets and sketches showing how he composed his masterpiece have been lost. Fortunately, he left behind enough clues to make it possible to give a plausible reconstruction of how he did it. Surprisingly, such a reconstruction has not been attempted before. In the winter of 1679, Robert Hooke initiated a correspondence with Newton outlining the physics of planetary motion. But Hooke was unable to formulate his concepts in mathematical form, and afterward, Newton accomplished this formulation, which allowed him to give a geometrical expression for the passage of time, thus laying the foundations for the Principia. On Dec.10, 1684, four months after a visit of Edmond Halley, Newton sent the first manuscripts for the Principia to the London Royal Society, which he had made "designedly abstruse to be understood only by able Mathematicians". This lack of clarity remains up to the present time. In his talk, I will show, however, that with simply a pencil and a ruler, and without any calculus, good approximations of orbits for central forces can be calculated graphically that also clarify the content of the Principia.


 

Aut. Qtr. Colloq. committee: R. Blandford (Chair), A. Kapitulnik, R. Laughlin, L. Senatore
Location: Hewlett Teaching Center, Rm. 200

Date and Time: 
Tuesday, October 23, 2018 - 4:30pm
Venue: 
Hewlett 200

Applied Physics/Physics Colloquium: Botswana to Bolivia - The Life of an Itinerant Science Educator

Topic: 
Botswana to Bolivia - The Life of an Itinerant Science Educator
Abstract / Description: 

Ranging across Botswana, Bolivia, Nepal, Denmark, The Navajo Nation, and small-town New Jersey, the intricacies of being an international science educator are explored. Does everyone think and communicate as "we" do? How can we maintain our sanity in an increasingly insane world? What are ways that we can best communicate scientific knowledge? These topics are explored in a web of poignant and often humorous anecdotes. The speaker, award-winning educator Phil Deutschle, holds degrees in Physics and Astronomy, is the author of, "The Two-Year Mountain: A Nepal Journey" and "Across African Sand: Journeys of a Witch-Doctor's Son-in-Law," and is the producer of the feature-length documentary, "Searching for Nepal."


 

Aut. Qtr. Colloq. committee: R. Blandford (Chair), A. Kapitulnik, R. Laughlin, L. Senatore
Location: Hewlett Teaching Center, Rm. 200

Date and Time: 
Tuesday, October 16, 2018 - 4:30pm
Venue: 
Hewlett 200

Applied Physics/Physics Colloquium: A High Energy View of the Extreme Universe

Topic: 
A High Energy View of the Extreme Universe
Abstract / Description: 

In the past 10 years, high energy gamma-ray astrophysics has undergone a renaissance. Dramatically improved capabilities from both ground based and space based observatories have combined to unveil dozens of new classes of gamma-ray emitters among the thousands of new sources, and studied each one with unprecedented spatial and spectral capabilities. Continuous monitoring of the high-energy gamma-ray sky has uncovered numerous outbursts from active galaxies, gamma-ray bursts and the discovery of transient sources in our galaxy – some with surprising counterparts. In this talk I will review some of the science highlights from the past decade with an emphasis on the surprises and remaining open questions.


 

Aut. Qtr. Colloq. committee: R. Blandford (Chair), A. Kapitulnik, R. Laughlin, L. Senatore
Location: Hewlett Teaching Center, Rm. 200

Date and Time: 
Tuesday, October 9, 2018 - 4:30pm
Venue: 
Hewlett 200

Pages

CS300 Seminar

Special Seminar: Formal Methods meets Machine Learning: Explorations in Cyber-Physical Systems Design

Topic: 
Formal Methods meets Machine Learning: Explorations in Cyber-Physical Systems Design
Abstract / Description: 

Cyber-physical systems (CPS) are computational systems tightly integrated with physical processes. Examples include modern automobiles, fly-by-wire aircraft, software-controlled medical devices, robots, and many more. In recent times, these systems have exploded in complexity due to the growing amount of software and networking integrated into physical environments via real-time control loops, as well as the growing use of machine learning and artificial intelligence (AI) techniques. At the same time, these systems must be designed with strong verifiable guarantees.

In this talk, I will describe our research explorations at the intersection of machine learning and formal methods that address some of the challenges in CPS design. First, I will describe how machine learning techniques can be blended with formal methods to address challenges in specification, design, and verification of industrial CPS. In particular, I will discuss the use of formal inductive synthesis --- algorithmic synthesis from examples with formal guarantees — for CPS design. Next, I will discuss how formal methods can be used to improve the level of assurance in systems that rely heavily on machine learning, such as autonomous vehicles using deep learning for perception. Both theory and industrial case studies will be discussed, with a special focus on the automotive domain. I will conclude with a brief discussion of the major remaining challenges posed by the use of machine learning and AI in CPS.

Date and Time: 
Monday, December 4, 2017 - 4:00pm
Venue: 
Gates 463A

SpaceX's journey on the road to mars

Topic: 
SpaceX's journey on the road to mars
Abstract / Description: 

SSI will be hosting Gwynne Shotwell — President and COO of SpaceX — to discuss SpaceX's journey on the road to mars. The event will be on Wednesday Oct 11th from 7pm - 8pm in Dinkelspiel Auditorium. After the talk, there will be a Q&A session hosted by Steve Jurvetson from DFJ Venture Capital.

Claim your tickets now on eventbright

 

Date and Time: 
Wednesday, October 11, 2017 - 7:00pm
Venue: 
Dinkelspiel Auditorium

CS Department Lecture Series (CS300)

Topic: 
Faculty speak about their research to new PhD students
Abstract / Description: 

Offered to incoming first-year PhD students in the Autumn quarter.

The seminar gives CS faculty the opportunity to speak about their research, which allows new CS PhD students the chance to learn about the professors and their research before permanently aligning.

4:30-5:15, Subhasish Mitra

5:15-6:00, Silvio Savarese

Date and Time: 
Wednesday, December 7, 2016 - 4:30pm to 6:00pm
Venue: 
200-305 Lane History Corner, Main Quad

CS Department Lecture Series (CS300)

Topic: 
Faculty speak about their research to new PhD students
Abstract / Description: 

Offered to incoming first-year PhD students in the Autumn quarter.

The seminar gives CS faculty the opportunity to speak about their research, which allows new CS PhD students the chance to learn about the professors and their research before permanently aligning.

4:30-5:15, Phil Levis

5:15-6:00, Ron Fedkiw

Date and Time: 
Monday, December 5, 2016 - 4:30pm to 6:00pm
Venue: 
200-305 Lane History Corner, Main Quad

CS Department Lecture Series (CS300)

Topic: 
Faculty speak about their research to new PhD students
Abstract / Description: 

Offered to incoming first-year PhD students in the Autumn quarter.

The seminar gives CS faculty the opportunity to speak about their research, which allows new CS PhD students the chance to learn about the professors and their research before permanently aligning.

4:30-5:15, Dan Boneh

5:15-6:00, Aaron Sidford

Date and Time: 
Wednesday, November 30, 2016 - 4:30pm to 6:00pm
Venue: 
200-305 Lane History Corner, Main Quad

CS Department Lecture Series (CS300)

Topic: 
Faculty speak about their research to new PhD students
Abstract / Description: 

Offered to incoming first-year PhD students in the Autumn quarter.

The seminar gives CS faculty the opportunity to speak about their research, which allows new CS PhD students the chance to learn about the professors and their research before permanently aligning.

4:30-5:15, John Mitchell

5:15-6:00, James Zou

Date and Time: 
Monday, November 28, 2016 - 4:30pm to 6:00pm
Venue: 
200-305 Lane History Corner, Main Quad

CS Department Lecture Series (CS300)

Topic: 
Faculty speak about their research to new PhD students
Abstract / Description: 

Offered to incoming first-year PhD students in the Autumn quarter.

The seminar gives CS faculty the opportunity to speak about their research, which allows new CS PhD students the chance to learn about the professors and their research before permanently aligning.

4:30-5:15, Emma Brunskill

5:15-6:00, Doug James

Date and Time: 
Wednesday, November 16, 2016 - 4:30pm to 6:00pm
Venue: 
200-305 Lane History Corner, Main Quad

CS Department Lecture Series (CS300)

Topic: 
Faculty speak about their research to new PhD students
Abstract / Description: 

Offered to incoming first-year PhD students in the Autumn quarter.

The seminar gives CS faculty the opportunity to speak about their research, which allows new CS PhD students the chance to learn about the professors and their research before permanently aligning.

4:30-5:15, James Landay

5:15-6:00, Dan Jurafsky

Date and Time: 
Monday, November 14, 2016 - 4:30pm to 6:00pm
Venue: 
200-305 Lane History Corner, Main Quad

CS Department Lecture Series (CS300)

Topic: 
Faculty speak about their research to new PhD students
Abstract / Description: 

Offered to incoming first-year PhD students in the Autumn quarter.

The seminar gives CS faculty the opportunity to speak about their research, which allows new CS PhD students the chance to learn about the professors and their research before permanently aligning.

4:30-5:15, Ken Salisbury

5:15-6:00, Noah Goodman

Date and Time: 
Wednesday, November 9, 2016 - 4:30pm to 6:00pm
Venue: 
200-305 Lane History Corner, Main Quad

CS Department Lecture Series (CS300)

Topic: 
Faculty speak about their research to new PhD students
Abstract / Description: 

Offered to incoming first-year PhD students in the Autumn quarter.

The seminar gives CS faculty the opportunity to speak about their research, which allows new CS PhD students the chance to learn about the professors and their research before permanently aligning.

4:30-5:15, Kunle Olukotun

5:15-6:00, Jure Leskovec

Date and Time: 
Monday, November 7, 2016 - 4:30pm to 6:00pm
Venue: 
200-305 Lane History Corner, Main Quad

Pages

EE380 Computer Systems Colloquium

EE380 Computer Systems Colloquium presents "Leela: a Semantic Intelligent Agent"

Topic: 
Leela: a Semantic Intelligent Agent
Abstract / Description: 

Leela is a semantic artificially intelligent agent modeled on the theories of Jean Piaget. She builds increasingly abstract semantic models of the world from her experiences of exploration, play, and experimentation. As an agent she is able to formulate, execute, and explain her own plans.

This talk will provide an introduction to Leela's background and design and will show her in action.

Date and Time: 
Wednesday, December 5, 2018 - 4:30pm
Venue: 
Gates B03

EE380 Computer Systems Colloquium presents "Safe passwords made easy to use"

Topic: 
Safe passwords made easy to use
Abstract / Description: 

How do we choose and remember our secure access codes? So far biometrics, password managers, and systems like Facebook connect have not been able to guarantee the security we need. Remembering dozens of different passwords becomes a usability nightmare. 25+ years into online experience, each of us have many hard-to-remember or easy-to-guess passwords, with all the risks and frustration they imply.

We describe experiments showing how to make easy to remember codes and passwords and the system to make them, called Cue-Pin-Select. It can generate (and regenerate) passwords on the go using only the user's brain for computation. It has the advantage of creating memorable passwords, not requiring any external storage or computing device, and can be executed in less than a minute to create a new password.

This talk will summarize recent usable security work done with Ted Selker. It will start with the Cue-Pin-Select algorithm, cover an improvement we found that applies to all passphrase-based security systems, and explain some of the work currently underway to have better tools to study password schemes and human computation.

Date and Time: 
Wednesday, November 28, 2018 - 4:30pm
Venue: 
Gates B03

EE380 Computer Systems Colloquium presents "How Behavior Spreads"

Topic: 
How Behavior Spreads
Abstract / Description: 

New social movements, technologies, and public-health initiatives often struggle to take off, yet many diseases disperse rapidly without issue. Can the lessons learned from the viral diffusion of diseases be used to improve the spread of beneficial behaviors and innovations? In this talk, I discuss several new breakthroughs in the science of network diffusion, and how these advances have improved our understanding of how changes in societal behavior--in voting, health, technology, and finance--occur, and the ways social networks can be used to influence how they propagate. The findings show that the same conditions accelerating the viral expansion of an epidemic unexpectedly inhibit the spread of behaviors. I show how many of the most well-known, intuitive ideas about how social networks function have in fact been responsible for causing past diffusion efforts to fail. I present new findings and new network methods that have been used to enable social change efforts to succeed much more effectively.

For futher reading please consult:

 

Date and Time: 
Wednesday, November 14, 2018 - 4:30pm
Venue: 
Gates B03

EE380 Computer Systems Colloquium presents "Partisan Gerrymandering and the Supreme Court: The Role of Social Science"

Topic: 
Partisan Gerrymandering and the Supreme Court: The Role of Social Science
Abstract / Description: 

***The talk for October 31, 2018 is drawn from our back list of videos and will not be a live presentation. This talk was originally given November 1, 2017. ***
We have been planning to have a speaker for this slot to address the issues of elections in a technological state. Despite many discussions and invitations, we have been unable to find anyone willing to take on speak about the current juncture of politics, technology, and economics.

The U.S. Supreme Court is considering a case this term, Gill v Whitford, that might lead to the first constitutional constraints on partisanship in redistricting. Eric McGhee is the inventor of the efficiency gap, a measure of gerrymandering that the court is considering in the case. He will describe the case's legal background, discuss some of the metrics that have been proposed for measuring gerrymandering, and reflect on the role of social science in the litigation.

Related NPR Science Friday Talk (Nov 3):

Does Math Have A Place In The Courtroom. Audio is 17 minutes.
So is it possible that these Ivy League-educated Supreme Court justices really don't understand the math of this case? Oliver Roeder, senior writer for FiveThirtyEight joins Ira to discuss whether the Supreme Court is allergic to math, and what that means for future cases. And Moon Duchin, associate professor of mathematics at Tufts University, returns to discuss the best math to use for rooting out gerrymandering.

Date and Time: 
Wednesday, October 31, 2018 - 4:30pm
Venue: 
Gates B03

EE380 Computer Systems Colloquium presents "Ten Arguments for Deleting Your Social Media Accounts Right Now and other thoughts about Internet"

Topic: 
Ten Arguments for Deleting Your Social Media Accounts Right Now and other thoughts about Internet
Abstract / Description: 

TBA

Date and Time: 
Wednesday, October 24, 2018 - 4:30pm
Venue: 
Gates B03

EE380 Computer Systems Colloquium: Efficient and Resilient Systems in the Cognitive Era

Topic: 
Efficient and Resilient Systems in the Cognitive Era
Abstract / Description: 

A focus on energy efficiency in the late CMOS design era, requires extra careful attention to system reliability and resilience to hardware-sourced errors. At the same time, the emergence of AI (cognitive) applications as a key growth segment is quite obvious. This talk will attempt to address the special challenges that next generation AI (or cognitive) systems pose, with a particular focus on next generation cognitive IoT architectures. We will discuss this primarily from the point of view of providing energy-efficient resilience in environments that are likely to have built-in vulnerability to errors. Such uncertainty stems not just from potentially error-prone (late CMOS) hardware designed for extreme efficiency, but also from algorithmic brittleness of the most prevalent forms of machine learning/deep learning (ML/DL) solution strategies today. In that context, we will briefly examine the promise of the Adaptive Swarm Intelligence (ASI) architectural paradigm that we have recently started investigating at IBM Research. This is a form of distributed or decentralized computing applied to the world of mobile cognitive IoT, backed by resilient support from back-end cloud (server) systems. In addition to examining the promises of inherent system architectural scalability and in-field, continuous learning that ASI offers, we will argue (albeit philosophically!) about why this could open the door to new models of self-aware systems that mimic cooperative and conscious problem solving in a human setting.


The Stanford EE Computer Systems Colloquium (EE380) meets on Wednesdays 4:30-5:45 throughout the academic year. Talks are given before a live audience in Room B03 in the basement of the Gates Computer Science Building on the Stanford Campus. The live talks (and the videos hosted at Stanford and on YouTube) are open to the public.

Stanford students may enroll in EE380 to take the Colloquium as a one unit S/NC class. Enrolled students are required to keep and electronic notebook or journal and to write a short, pithy comment about each of the ten lectures and a short free form evaluation of the class in order to receive credit. Assignments are due at the end of the quarter, on the last day of examinations.

EE380 is a video class. Live attendance is encouraged but not required. We (the organizers) feel that watching the video is not a substitute for being present in the classroom. Questions are encouraged.

Many past EE380 talks are available on YouTube, see the EE380 Playlist.

Date and Time: 
Wednesday, October 3, 2018 - 4:30pm
Venue: 
Gates B03

EE380 Computer Systems Colloquium: The Case for Learned Index Structures

Topic: 
The Case for Learned Index Structures
Abstract / Description: 

Indexes are models: a B-Tree-Index can be seen as a model to map a key to the position of a record within a sorted array, a Hash-Index as a model to map a key to a position of a record within an unsorted array, and a BitMap-Index as a model to indicate if a data record exists or not. In this talk, we take this premise and explain how existing database index structures can be replaced with other types of models, which we term learned indexes. The key idea is that a model can learn the sort order or structure of indexed data and use this signal to effectively predict the position or existence of records. We offer theoretical analysis under which conditions learned indexes outperform traditional index structures and we will delve into the challenges in designing learned index structures. Through addressing these challenges, our initial results show that learned indexes are able to outperform cache-optimized B-Trees by up to 70% in speed while saving an order-of-magnitude in memory over several real-world data sets. Finally, we will discuss the broader implications of learned indexes on database design and future directions for the ML for Database Systems research.


The Stanford EE Computer Systems Colloquium (EE380) meets on Wednesdays 4:30-5:45 throughout the academic year. Talks are given before a live audience in Room B03 in the basement of the Gates Computer Science Building on the Stanford Campus. The live talks (and the videos hosted at Stanford and on YouTube) are open to the public.

Stanford students may enroll in EE380 to take the Colloquium as a one unit S/NC class. Enrolled students are required to keep and electronic notebook or journal and to write a short, pithy comment about each of the ten lectures and a short free form evaluation of the class in order to receive credit. Assignments are due at the end of the quarter, on the last day of examinations.

EE380 is a video class. Live attendance is encouraged but not required. We (the organizers) feel that watching the video is not a substitute for being present in the classroom. Questions are encouraged.

Many past EE380 talks are available on YouTube, see the EE380 Playlist.

Date and Time: 
Wednesday, October 17, 2018 - 4:30pm
Venue: 
Gates B03

EE380 Computer Systems Colloquium: 2017 Turing Award Recipients on Computer Architecture

Topic: 
Computer Architecture
Abstract / Description: 

TBA


The Stanford EE Computer Systems Colloquium (EE380) meets on Wednesdays 4:30-5:45 throughout the academic year. Talks are given before a live audience in Room B03 in the basement of the Gates Computer Science Building on the Stanford Campus. The live talks (and the videos hosted at Stanford and on YouTube) are open to the public.

Stanford students may enroll in EE380 to take the Colloquium as a one unit S/NC class. Enrolled students are required to keep and electronic notebook or journal and to write a short, pithy comment about each of the ten lectures and a short free form evaluation of the class in order to receive credit. Assignments are due at the end of the quarter, on the last day of examinations.

EE380 is a video class. Live attendance is encouraged but not required. We (the organizers) feel that watching the video is not a substitute for being present in the classroom. Questions are encouraged.

Many past EE380 talks are available on YouTube, see the EE380 Playlist.

Date and Time: 
Wednesday, October 10, 2018 - 4:30pm
Venue: 
Gates B03

EE380 Computer Systems Colloquium: Interactive Autonomy: a human-centered approach for safe interactions

Topic: 
Interactive Autonomy: a human-centered approach for safe interactions
Abstract / Description: 

Today's society is rapidly advancing towards robotics systems that interact and collaborate with humans, e.g., semi-autonomous vehicles interacting with drivers and pedestrians, medical robots used in collaboration with doctors, or service robots interacting with their users in smart homes. In this talk, I will first discuss interactive autonomy, where we develop algorithms for autonomous systems that influence humans, and further leverage these effects for better safety, efficiency, coordination, and estimation. I will then focus on our efficient active learning methods to build predictive models of humans's preferences by eliciting comparisons from a mixed set of humans, and further analyzing the generalizability and robustness of the learned human models for safe and seamless interaction with robots.


The Stanford EE Computer Systems Colloquium (EE380) meets on Wednesdays 4:30-5:45 throughout the academic year. Talks are given before a live audience in Room B03 in the basement of the Gates Computer Science Building on the Stanford Campus. The live talks (and the videos hosted at Stanford and on YouTube) are open to the public.

Stanford students may enroll in EE380 to take the Colloquium as a one unit S/NC class. Enrolled students are required to keep and electronic notebook or journal and to write a short, pithy comment about each of the ten lectures and a short free form evaluation of the class in order to receive credit. Assignments are due at the end of the quarter, on the last day of examinations.

EE380 is a video class. Live attendance is encouraged but not required. We (the organizers) feel that watching the video is not a substitute for being present in the classroom. Questions are encouraged.

Many past EE380 talks are available on YouTube, see the EE380 Playlist.

Date and Time: 
Wednesday, September 26, 2018 - 4:30pm
Venue: 
Gates B03

EE380 Computer Systems Colloquium presents Optional Static Typing for Python

Topic: 
Optional Static Typing for Python
Abstract / Description: 

Python is a dynamically typed language, and some of its appeal derives from this. Nevertheless, especially for large code bases, it would be nice if a compiler could find type errors before the code is even run. Optional static type checking promises exactly this, and over the past four years we have successfully introduced this feature into Python 3. This talk introduces the type system we've adopted and the syntax used for type annotations, some tips on how to get started with a large existing code base, and our experience using the 'mypy' type checker at Dropbox. The entire system is open source, and has also been adopted by other companies such as Lyft, Quora and Facebook.

Date and Time: 
Wednesday, June 6, 2018 - 4:30pm
Venue: 
Gates B03

Pages

Ginzton Lab

AP483, Ginzton Lab, & AMO Seminar Series presents "Quantum Electrodynamics of Superconducting Circuits"

Topic: 
Quantum Electrodynamics of Superconducting Circuits
Abstract / Description: 

The demand for rapid and high-fidelity execution of initialization, gate and read-out operations casts tight constraints on the accuracy of quantum electrodynamic modeling of superconducting integrated circuits. Attaining the required accuracies requires reconsidering our basic approach to the quantization of the electromagnetic field in a light-confining medium and the notion of normal modes. I will discuss a computational framework based on the Heisenberg-Langevin approach to address these fundamental questions. This framework allows the accurate determination of the quantum dynamics of a superconducting qubit in an arbitrarily complex electromagnetic environment, free of divergences that have plagued earlier approaches. I will also discuss the effectiveness of this computational approach in meeting the demands of present-day quantum computing research.


Academic year 2018-2019, please join us at Spilker room 232 every Monday afternoon from 4 pm for the AP 483 & Ginzton Lab, and AMO Seminar Series.

Refreshments begin at 4 pm, seminar at 4:15 pm.

Date and Time: 
Monday, December 3, 2018 - 4:15pm
Venue: 
Spilker 232

AP483, Ginzton Lab, & AMO Seminar Series

Topic: 
When quantum-information scrambling met quasiprobabilities
Abstract / Description: 

We do physics partially out of a drive to understand essences. One topic whose essence merits understanding is the out-of-time-ordered correlator (OTOC). The OTOC reflects quantum manybody thermalization, chaos, and scrambling (the spread of quantum information through manybody entanglement). The OTOC, I will show, equals an average over a quasiprobability distribution. A quasiprobability resembles a probability but can become negative and nonreal. Such nonclassical values can signal nonclassical physics. The OTOC quasiprobability has several applications: Experimentally, the quasiprobability points to a scheme for measuring the OTOC (via weak measurements, which refrain from disturbing the measured system much). The quasiprobability also signals false positives in attempts to measure scrambling of open systems. Theoretically, the quasiprobability links the OTOC to uncertainty relations, to nonequilibrium statistical mechanics, and more strongly to chaos. As coarse-graining the quasiprobability yields the OTOC, the quasiprobability forms the OTOC's essence.

References
• NYH, Phys. Rev. A 95, 012120 (2017). https://journals.aps.org/pra/abstract/10.1103/PhysRevA.95.012120
• NYH, Swingle, and Dressel, Phys. Rev. A 97, 042105 (2018). https://journals.aps.org/pra/abstract/10.1103/PhysRevA.97.042105
• NYH, Bartolotta, and Pollack, arXiv:1806.04147 (2018). https://arxiv.org/abs/1806.04147
• Gonzàlez Alonso, NYH, and Dressel, arXiv:1806.09637 (2018). https://arxiv.org/abs/1806.09637
• Swingle and NYH, Phys. Rev. A 97, 062113 (2018). https://journals.aps.org/pra/abstract/10.1103/PhysRevA.97.062113
• Dressel, Gonzàlez Alonso, Waegell, and NYH, Phys. Rev. A 98, 012132 (2018). https://journals.aps.org/pra/abstract/10.1103/PhysRevA.98.012132


Academic year 2018-2019, please join us at Spilker room 232 every Monday afternoon from 4 pm for the AP 483 & Ginzton Lab, and AMO Seminar Series.

Refreshments begin at 4 pm, seminar at 4:15 pm.

Date and Time: 
Monday, November 12, 2018 - 4:15pm
Venue: 
Spilker 232

AP483, Ginzton Lab, & AMO Seminar Series presents Conductivity of a perfect crystal

Topic: 
Conductivity of a perfect crystal
Abstract / Description: 

Dissipation of electrical current in typical metals is due to scattering off material defects and phonons. But what if the material were a perfect crystal, and sufficiently stiff or cold to eliminate phonons -- would conductivity become infinite? We realize an analogous scenario with atomic fermions in a cubic optical lattice, and measure conductivity. The equivalent of Ohm's law for neutral particles gives conductivity as the ratio of particle current to the strength of an applied force. Our measurements are at non-zero frequency (since a trapping potential prevents dc current flow), giving the low-frequency spectrum of real and imaginary conductivity. Since our atoms carry no charge, we measure particle currents with in-situ microscopy, with which both on- and off-diagonal response is visible. Sum rules are used to relate the observed conductivity to thermodynamic properties such as kinetic energy. We explore the effect of lattice depth, temperature, interaction strength, and atom number on conductivity. Using a relaxation-time approximation, we extract the transport time, i.e., the relaxation rate of current through collisions. Returning to the initial question, we demonstrate that fermion-fermion collisions damp current since the lattice breaks Galilean invariance.


Academic year 2018-2019, please join us at Spilker room 232 every Monday afternoon from 4 pm for the AP 483 & Ginzton Lab, and AMO Seminar Series.

Refreshments begin at 4 pm, seminar at 4:15 pm.

Date and Time: 
Monday, October 29, 2018 - 4:15pm
Venue: 
Spilker 232

AP483, Ginzton Lab, & AMO Seminar Series

Topic: 
New opportunities with old photonic materials
Abstract / Description: 

 Lithium niobate (LN) is an "old" material with many applications in optical and microwave technologies, owing to its unique properties that include large second order nonlinear susceptibility, large piezoelectric response, and wide optical transparency window. Conventional LN components, including modulators and periodically polled frequency converters, have been the workhorse of the optoelectronic industry. They are reaching their limits, however, as they rely on weakly guiding ion-diffusion defined optical waveguides in bulk LN crystal. I will discuss our efforts aimed at the development of integrated LN platform, featuring sub-wavelength scale light confinement and dense integration of optical and electrical components, that has the potential to revolutionize optical communication networks and microwave photonic systems, as well as enable realization of quantum photonic circuits. Good example is our recently demonstrated integrated LN electro-optic modulator that can be driven directly by a CMOS circuit, that supports data rates > 200 gigabits per second with > 90% optical transmission efficiency. I will also discuss our work on ultra-high Q LN optical cavities (Q ~ 10,000,000) and their applications, as well as nonlinear wavelength conversion using different approaches based on LN films.
Diamond is another "old" material with remarkable properties! It is transparent from the ultra-violet to infrared, has a high refractive index, strong optical nonlinearity and a wide variety of light-emitting defects of interest for quantum communication and computation. In my talk, I will summarize our efforts towards the development of integrated diamond quantum photonics platform aimed at realization of efficient photonic and phononic interfaces for diamond spin qubits.


 

Academic year 2018-2019, please join us at Spilker room 232 every Monday afternoon from 4 pm for the AP 483 & Ginzton Lab, and AMO Seminar Series.

Refreshments begin at 4 pm, seminar at 4:15 pm.

Date and Time: 
Monday, October 22, 2018 - 4:15pm
Venue: 
Spilker 232

AP483, Ginzton Lab, & AMO Seminar Series presents Dynamic photonic structures

Topic: 
Dynamic photonic structures: non-reciprocity, gauge potential, and synthetic dimensions.
Abstract / Description: 

 

We show that dynamic photonic structures, where refractive index of the structure is modulated as a function of time, offers a wide ranges of possibilities for exploration of physics and applications of light. In particular, dynamic photonic structures naturally break reciprocity. With proper design such photonic structure can then be used to achieve complete optical isolation and to completely reproduce magneto-optical effects without the use of gyrotropic materials. Moreover, the phase of the modulation corresponds to an effective magnetic gauge potential for photons, through which one can explore a wide variety of fundamental physics effects of synthetic magnetic field using photons. Finally, such dynamic photonic structure can be used to explore physics, especially topological physics, in dimensions that are higher than the physical dimension of the structure, leading to intriguing possibilities in manipulation of the frequencies of light in non-trivial ways.


 

Academic year 2018-2019, please join us at Spilker room 232 every Monday afternoon from 4 pm for the AP 483 & Ginzton Lab, and AMO Seminar Series.

Refreshments begin at 4 pm, seminar at 4:15 pm.

Date and Time: 
Monday, October 15, 2018 - 4:15pm
Venue: 
Spilker 232

New Directions in Management Science & Engineering: A Brief History of the Virtual Lab

Topic: 
New Directions in Management Science & Engineering: A Brief History of the Virtual Lab
Abstract / Description: 

Lab experiments have long played an important role in behavioral science, in part because they allow for carefully designed tests of theory, and in part because randomized assignment facilitates identification of causal effects. At the same time, lab experiments have traditionally suffered from numerous constraints (e.g. short duration, small-scale, unrepresentative subjects, simplistic design, etc.) that limit their external validity. In this talk I describe how the web in general—and crowdsourcing sites like Amazon's Mechanical Turk in particular—allow researchers to create "virtual labs" in which they can conduct behavioral experiments of a scale, duration, and realism that far exceed what is possible in physical labs. To illustrate, I describe some recent experiments that showcase the advantages of virtual labs, as well as some of the limitations. I then discuss how this relatively new experimental capability may unfold in the future, along with some implications for social and behavioral science.

Date and Time: 
Thursday, March 16, 2017 - 12:15pm
Venue: 
Packard 101

Claude E. Shannon's 100th Birthday

Topic: 
Centennial year of the 'Father of the Information Age'
Abstract / Description: 

From UCLA Shannon Centennial Celebration website:

Claude Shannon was an American mathematician, electrical engineer, and cryptographer known as "the father of information theory". Shannon founded information theory and is perhaps equally well known for founding both digital computer and digital circuit design theory. Shannon also laid the foundations of cryptography and did basic work on code breaking and secure telecommunications.

 

Events taking place around the world are listed at IEEE Information Theory Society.

Date and Time: 
Saturday, April 30, 2016 - 12:00pm
Venue: 
N/A

Ginzton Lab / AMO Seminar

Topic: 
2D/3D Photonic Integration Technologies for Arbitrary Optical Waveform Generation in Temporal, Spectral, and Spatial Domains
Abstract / Description: 

Beginning Academic year 2015-2016, please join us at Spilker room 232 every Monday afternoon from 4 pm for the AP 483 & Ginzton Lab, and AMO Seminar Series.

Refreshments begin at 4 pm, seminar at 4:15 pm.

Date and Time: 
Monday, February 29, 2016 - 4:15pm to 5:15pm
Venue: 
Spilker 232

Ginzton Lab / AMO Seminar

Topic: 
Silicon-Plus Photonics for Tomorrow's (Astronomically) Large-Scale Networks
Abstract / Description: 

Beginning Academic year 2015-2016, please join us at Spilker room 232 every Monday afternoon from 4 pm for the AP 483 & Ginzton Lab, and AMO Seminar Series.

Refreshments begin at 4 pm, seminar at 4:15 pm.

Date and Time: 
Monday, February 22, 2016 - 4:15pm to 5:15pm
Venue: 
Spilker 232

Pages

Information Systems Lab (ISL) Colloquium

CANCELLED! ISL & IT Forum present "Bayesian Suffix Trees: Learning and Using Discrete Time Series"

Topic: 
CANCELLED! Bayesian Suffix Trees: Learning and Using Discrete Time Series
Abstract / Description: 

CANCELLED!  We apologize for any inconvenience.

One of the main obstacles in the development of effective algorithms for inference and learning from discrete time series data, is the difficulty encountered in the identification of useful temporal structure. We will discuss a class of novel methodological tools for effective Bayesian inference and model selection for general discrete time series, which offer promising results on both small and big data. Our starting point is the development of a rich class of Bayesian hierarchical models for variable-memory Markov chains. The particular prior structure we adopt makes it possible to design effective, linear-time algorithms that can compute most of the important features of the resulting posterior and predictive distributions without resorting to MCMC. We have applied the resulting tools to numerous application-specific tasks, including on-line prediction, segmentation, classification, anomaly detection, entropy estimation, and causality testing, on data sets from different areas of application, including data compression, neuroscience, finance, genetics, and animal communication. Results on both simulated and real data will be presented.

Date and Time: 
Wednesday, December 12, 2018 - 3:00pm
Venue: 
Packard 202

ISL Colloquium presents "Information-theoretic Privacy"

Topic: 
Information-theoretic Privacy: A holistic view via leakage measures, robust privacy guarantees, and adversarial models for mechanism design
Abstract / Description: 

Privacy is the problem of ensuring limited leakage of information about sensitive features while sharing information (utility) about non-private features to legitimate data users. Even as differential privacy has emerged as a strong desideratum for privacy, there is a need for varied yet rigorous approaches for applications with different requirements. This talk presents an information-theoretic approach and takes a holistic view focusing on leakage measures, design of privacy mechanisms, and verifiable implementations using generative adversarial models. Specifically, we introduce maximal alpha leakage as a new class of adversarially motivated tunable leakage measures that quantifies the maximal gain of an adversary in refining a tilted belief of any (potentially random) function of a dataset conditioned on a disclosed dataset. The choice of alpha determines the specific adversarial action ranging from refining a belief for alpha = 1 to guessing the best posterior for alpha = ∞, and for these extremal values this measure simplifies to mutual information (MI) and maximal leakage (MaxL), respectively. The problem of guaranteeing privacy can then be viewed as one of designing a randomizing mechanism that minimizes alpha leakage subject to utility constraints. We then present bounds on the robustness of privacy guarantees that can be made when designing mechanisms from a finite number of samples. Finally, we focus on a data-driven approach, generative adversarial privacy (GAP), to design privacy mechanisms using neural networks. GAP is modeled as a constrained minimax game between a privatizer (intent on publishing a utility-guaranteeing learning representation that limits leakage of the sensitive features) and an adversary (intent on learning the sensitive features). We demonstrate the performance of GAP on multi-dimensional Gaussian mixture models and the GENKI dataset. Time permitting, we will briefly discuss the learning-theoretic underpinnings of GAP as well as connections to the problem of algorithmic fairness.

This work is a result of multiple collaborations: (a) maximal alpha leakage with J. Liao (ASU), O. Kosut (ASU), and F. P. Calmon (Harvard); (b) robust mechanism design with M. Diaz (ASU), H. Wang (Harvard), and F. P. Calmon (Harvard); and (c) GAP with C. Huang (ASU), P. Kairouz (Google), X. Chen (Stanford), and R. Rajagopal (Stanford).

Date and Time: 
Wednesday, December 5, 2018 - 4:15pm
Venue: 
Packard 202

ISL Colloquium presents "Estimation After Parameter Selection"

Topic: 
Estimation After Parameter Selection
Abstract / Description: 

In many practical parameter estimation problems, such as medical experiments and cognitive radio communications, parameter selection is performed prior to estimation. The selection process has a major impact on subsequent estimation by introducing a selection bias and creating coupling between decoupled parameters. As a result, classical estimation theory may be inappropriate and inaccurate and a new methodology is needed. In this study, the problem of estimating a preselected unknown deterministic parameter, chosen from a parameter set based on a predetermined data-based selection rule, Ψ, is considered. In this talk, I will present a general non-Bayesian estimation theory for estimation after parameter selection, includes estimation methods, performance analysis, and adaptive sampling strategies. The new theory is based on the post-selection mean-square-error (PSMSE) criterion as a performance measure instead of the commonly used mean-square-error (MSE). We derive the corresponding Cramér-Rao-type bound on the PSMSE of any Ψ-unbiased estimator, where the Ψ -unbiasedness is in the Lehmann-unbiasedness sense. Then, the post-selection maximum-likelihood (PSML) estimator is presented and its Ψ–efficiency properties are demonstrated. Practical implementations of the PSML estimator are proposed as well. As time permits, I will discuss the similar ideas that can be applied to estimation after model selection and to estimation in Good-Turing models.

Date and Time: 
Monday, December 3, 2018 - 4:15pm
Venue: 
Packard 101

ISL Colloquium presents Transportation Systems Resilience: Capacity-Aware Control and Value of Information

Topic: 
Transportation Systems Resilience: Capacity-Aware Control and Value of Information
Abstract / Description: 

Resilience of a transportation system is its ability to operate under adverse events like incidents and storms. Availability of real-time traffic data provides new opportunities for predicting travelers' routing behavior and implementing network control operations during adverse events. In this talk, we will discuss two problems: controlling highway corridors in response to disruptions and modeling strategic route choices of travelers with heterogeneous access to incident information. Firstly, we present an approach to designing control strategies for highway corridors facing stochastic capacity disruptions such random incidents and vehicle platoons/moving bottlenecks. We exploit the properties of traffic flow dynamics under recurrent incidents to derive verifiable conditions for stability of traffic queues, and also obtain guarantees on the system throughput. Secondly, we introduce a routing game in which travelers receive asymmetric and incomplete information about uncertain network state, and make route choices based on their private beliefs about the state and other travelers' behavior. We study the effects of information heterogeneity on travelers' equilibrium route choices and costs. Our analysis is useful for evaluating the value of receiving state information for travelers, which can be positive, zero, or negative in equilibrium. These results demonstrate the advantages of considering network state uncertainty in both strategic and operational aspects of system resilience.

Date and Time: 
Friday, November 30, 2018 - 4:15pm
Venue: 
Packard 101

ISL Colloquium presents Deconstructing the Blockchain to Approach Physical Limits

Topic: 
Deconstructing the Blockchain to Approach Physical Limits
Abstract / Description: 

The concept of a blockchain was invented by Satoshi Nakamoto to maintain a distributed ledger for an electronic payment system, Bitcoin. In addition to its security, important performance measures of a blockchain protocol are its transaction throughput, confirmation latency and confirmation reliability. These measures are limited by two underlying physical network attributes: communication capacity and speed-of-light propagation delay. Existing systems operate far away from these physical limits. In this work we introduce Prism, a new blockchain protocol, which can provably achieve 1) security against up to 50% adversarial hashing power; 2) optimal throughput up to the capacity C of the network; 3) confirmation latency for honest transactions proportional to the propagation delay D, with confirmation error probability exponentially small in the bandwidth-delay product CD; 4) eventual total ordering of all transactions. Our approach to the design of this protocol is based on deconstructing the blockchain into its basic functionalities and systematically scaling up these functionalities to approach their physical limits.

This is joint work with Vivek Bagaria, David Tse, Giulia Fanti and Pramod Viswanath. The full paper can be found here.

Date and Time: 
Thursday, November 29, 2018 - 3:00pm
Venue: 
Packard 101

ISL Colloquium presents Artwork Personalization via Online Learning

Topic: 
Artwork Personalization via Online Learning
Abstract / Description: 

For many years, the main goal of the Netflix recommendation engine has been to get the right titles in front of each member at the right time. Today, we use nonlinear, probabilistic and deep learning approaches to make better and better rankings of our movies and TV shows for each user. But the job of recommendation does not end there. The homepage should be able to convey to the member enough evidence of why this is a good title for her, especially for shows that the member has never heard of. One way to address this challenge is to personalize the way we portray the titles on our service. Our image personalization engine is driven by online learning and contextual bandits. Traditional bandits frameworks make strong assumptions which do not apply when predictions entail actions in the real world. We will discuss how learning algorithms can be augmented to better deal with causality, bias, and noncompliance.

Date and Time: 
Tuesday, November 13, 2018 - 4:15pm
Venue: 
Packard 202

ISL Colloquium presents Estimating the Information Flow in Deep Neural Networks

Topic: 
Estimating the Information Flow in Deep Neural Networks
Abstract / Description: 

This talk will discuss the flow of information and the evolution of internal representations during deep neural network (DNN) training, aiming to demystify the compression aspect of the information bottleneck theory. The theory suggests that DNN training comprises a rapid fitting phase followed by a slower compression phase, in which the mutual information I(X;T) between the input X and internal representations T decreases. Several papers observe compression of estimated mutual information on different DNN models, but the true I(X;T) over these networks is provably either constant (discrete X) or infinite (continuous X). We will explain this discrepancy between theory and experiments, and explain what was actually measured by these past works.

To this end, an auxiliary (noisy) DNN framework will be introduced, in which I(X;T) is a meaningful quantity that depends on the network's parameters. We will show that this noisy framework is a good proxy for the original (deterministic) system both in terms of performance and the learned representations. To accurately track I(X;T) over noisy DNNs, a differential entropy estimator tailor to exploit the DNN's layered structure will be developed and theoretical guarantees on the associated minimax risk will be provided. Using this estimator along with a certain analogy to an information-theoretic communication problem, we will elucidate the geometric mechanism that drives compression of I(X;T) in noisy DNNs. Based on these findings, we will circle back to deterministic networks and explain what the past observations of compression were in fact showing. Future research directions inspired by this study aiming to facilitate a comprehensive information-theoretic understanding of deep learning will also be discussed.

Date and Time: 
Friday, November 9, 2018 - 1:15pm
Venue: 
Packard 202

ISL Colloquium presents When do neural networks have bad local minima, and when not?

Topic: 
When do neural networks have bad local minima, and when not?
Abstract / Description: 

To explain the recent success of neural networks, researchers have conjectured that all local minima are global minima despite the non-convexity of the problem. Is this really true? Is this just hand-wavy intuition that is roughly true in special cases or can be a rigorous result in a broad setting?

In this talk, instead of explaining "why neural-nets are good", we try to understand "when neural-nets are good, and when not" --with a restricted definition of "good" by "every local-min is global-min". We focus on the binary classification problem and discuss how architecture and data affect the landscape. On the positive side, we prove that no bad local minima exist under reasonable assumptions on the neuron types, the neural-net structure, the loss function, and the dataset. On the negative side, we provide dozens of counterexamples that show the necessity of most assumptions.

Our approach can be viewed as a game of "local-min attack" and "defense". An attacker tries to construct examples that bad local minima exist, and the defender modifies the setting to eliminate bad local minima. For instance, the attacker constructs bad local minima for 1-hidden-layer ReLU network with linearly separable data, then the defender proves that smooth versions of ReLU eliminate them. At last, we present a strong defense consisting of a special neuron and a special regularizer that can eliminate bad local minima for a deep neural-net in the realizable case.

Joint work with Shiyu Liang, Yixuan Li, Jason Lee and R. Srikant.

Date and Time: 
Thursday, November 8, 2018 - 4:15pm
Venue: 
Packard 101

ISL Colloquium presents Taming the Devil of Gradient-based Optimization Methods with the Angel of Differential Equations

Topic: 
Taming the Devil of Gradient-based Optimization Methods with the Angel of Differential Equations
Abstract / Description: 

In this talk, we use ordinary differential equations to model, analyze, and interpret gradient-based optimization methods. In the first part of the talk, we derive a second-order ODE that is the limit of Nesterov's accelerated gradient method for non-strongly objectives (NAG-C). The continuous-time ODE is shown to allow for a better understanding of NAG-C and, as a byproduct, we obtain a family of accelerated methods with similar convergence rates. In the second part, we begin by recognizing that existing ODEs in the literature are inadequate to distinguish between two fundamentally different methods, Nesterov's accelerated gradient method for strongly convex functions (NAG-SC) and Polyak's heavy-ball method. In response, we derive high-resolution ODEs as more accurate surrogates for the three aforementioned methods. These novel ODEs can be integrated into a general framework that allows for a fine-grained analysis of the discrete optimization algorithms through translating properties of the amenable ODEs into those of their discrete counterparts. As the first application of this framework, we identify the effect of a term referred to as 'gradient correction' in NAG-SC but not in the heavy-ball method, shedding insight into why the former achieves acceleration while the latter does not. Moreover, in this high-resolution ODE framework, NAG-C is shown to boost the squared gradient norm minimization at the inverse cubic rate, which is the sharpest known rate concerning NAG-C itself. Finally, by modifying the high-resolution ODE of NAG-C, we obtain a family of new optimization methods that are shown to maintain the accelerated convergence rates as NAG-C for smooth convex functions. This is based on joint work with Stephen Boyd, Emmanuel Candes, Simon Du, Michael Jordan, and Bin Shi.

Date and Time: 
Thursday, November 1, 2018 - 4:15pm
Venue: 
Packard 101

ISL Colloquium: Battling Demons in Peer Review

Topic: 
New Battling Demons in Peer Review
Abstract / Description: 

Peer review is the backbone of scholarly research. It is however faced with a number of challenges (or "demons") such as subjectivity, bias/miscalibration, noise, and strategic behavior. The growing number of submissions in many areas of research such as machine learning has significantly increased the scale of these demons. This talk will present some principled and practical approaches to battle these demons in peer review:

(1) Subjectivity: How to ensure that all papers are judged by the same yardstick?

(2) Bias/miscalibration: How to use ratings in presence of arbitrary or adversarial miscalibration?

(3) Noise: How to assign reviewers to papers to simultaneously ensure fair and accurate evaluations in the presence of review noise?

(4) Strategic behavior: How to insulate peer review from strategic behavior of author-reviewers?

The work uses tools from statistics and learning theory, social choice theory, information theory, game theory and decision theory. (No prior knowledge on these topics will be assumed.)


The Information Theory Forum (IT-Forum) at Stanford ISL is an interdisciplinary academic forum which focuses on mathematical aspects of information processing. With a primary emphasis on information theory, we also welcome researchers from signal processing, learning and statistical inference, control and optimization to deliver talks at our forum. We also warmly welcome industrial affiliates in the above fields. The forum is typically held in Packard 202 every Thursday at 4:15 pm during the academic year.

The Information Theory Forum is organized by graduate students Martin Zhang, Farzan Farnia, and Zhengyuan Zhou. To suggest speakers, please contact any of the students.

Date and Time: 
Thursday, October 25, 2018 - 4:15pm
Venue: 
Packard 202

Pages

IT-Forum

CANCELLED! ISL & IT Forum present "Bayesian Suffix Trees: Learning and Using Discrete Time Series"

Topic: 
CANCELLED! Bayesian Suffix Trees: Learning and Using Discrete Time Series
Abstract / Description: 

CANCELLED!  We apologize for any inconvenience.

One of the main obstacles in the development of effective algorithms for inference and learning from discrete time series data, is the difficulty encountered in the identification of useful temporal structure. We will discuss a class of novel methodological tools for effective Bayesian inference and model selection for general discrete time series, which offer promising results on both small and big data. Our starting point is the development of a rich class of Bayesian hierarchical models for variable-memory Markov chains. The particular prior structure we adopt makes it possible to design effective, linear-time algorithms that can compute most of the important features of the resulting posterior and predictive distributions without resorting to MCMC. We have applied the resulting tools to numerous application-specific tasks, including on-line prediction, segmentation, classification, anomaly detection, entropy estimation, and causality testing, on data sets from different areas of application, including data compression, neuroscience, finance, genetics, and animal communication. Results on both simulated and real data will be presented.

Date and Time: 
Wednesday, December 12, 2018 - 3:00pm
Venue: 
Packard 202

IT Forum presents "Perceptual Engineering"

Topic: 
Perceptual Engineering
Abstract / Description: 

The distance between the real and the digital is clearest at the interface layer. The ways that our bodies interact with the physical world are rich and elaborate while digital interactions are far more limited. Through an increased level of direct and intuitive interaction, my work aims to raise computing devices from external systems that require deliberate usage to those that are truly an extension of us, advancing both the state of research and human ability. My approach is to use the entire body for input and output, to allow for implicit and natural interactions. I call my concept "perceptual engineering," i.e., a method to alter the user's perception (or more specifically the input signals to their perception) and manipulate it in subtle ways. For example, modifying a user's sense of space, place, balance and orientation or manipulating their visual attention, all without the user's explicit input, and in order to assist or guide their interactive experience in an effortless way.

I build devices and immersive systems that explore the use of cognitive illusions to manage attention, physiological signals for interaction, deep learning for automatic VR generation, embodiment for remote collaborative learning, tangible interaction for augmenting play, haptics for enhancing immersion, and vestibular stimulation to mitigate motion sickness in VR. My "perceptual engineering" approach has been shown to, (1) support implicit and natural interactions with haptic feedback, (2) induce believable physical sensations of motion in VR, (3) provide a novel way to communicate with the user through proprioception and kinesthesia, and (4) serve as a platform to question the boundaries of our sense of agency and trust. For decades, interaction design has been driven to answer the question: how can new technologies allow users to interact with digital content in the most natural way? If we look at the evolution of computing over the last 50 years, interaction has gone from punch cards to mouse and keyboard to touch and voice. Similarly, devices have become smaller and closer to the user's body. With every transition, the things people can do have become more personal. The main question that drives my research is: what is the next logical step?

Date and Time: 
Friday, December 7, 2018 - 1:15pm
Venue: 
Packard 202

IT-Forum presents Estimating the Information Flow in Deep Neural Networks

Topic: 
Estimating the Information Flow in Deep Neural Networks
Abstract / Description: 

This talk will discuss the flow of information and the evolution of internal representations during deep neural network (DNN) training, aiming to demystify the compression aspect of the information bottleneck theory. The theory suggests that DNN training comprises a rapid fitting phase followed by a slower compression phase, in which the mutual information I(X;T) between the input X and internal representations T decreases. Several papers observe compression of estimated mutual information on different DNN models, but the true I(X;T) over these networks is provably either constant (discrete X) or infinite (continuous X). We will explain this discrepancy between theory and experiments, and explain what was actually measured by these past works.

To this end, an auxiliary (noisy) DNN framework will be introduced, in which I(X;T) is a meaningful quantity that depends on the network's parameters. We will show that this noisy framework is a good proxy for the original (deterministic) system both in terms of performance and the learned representations. To accurately track I(X;T) over noisy DNNs, a differential entropy estimator tailor to exploit the DNN's layered structure will be developed and theoretical guarantees on the associated minimax risk will be provided. Using this estimator along with a certain analogy to an information-theoretic communication problem, we will elucidate the geometric mechanism that drives compression of I(X;T) in noisy DNNs. Based on these findings, we will circle back to deterministic networks and explain what the past observations of compression were in fact showing. Future research directions inspired by this study aiming to facilitate a comprehensive information-theoretic understanding of deep learning will also be discussed.

Date and Time: 
Wednesday, October 31, 2018 - 1:15pm
Venue: 
Packard 202

IT-Forum presents Uncoupled isotonic regression and Wasserstein deconvolution

Topic: 
Uncoupled isotonic regression and Wasserstein deconvolution
Abstract / Description: 

Isotonic regression is a standard problem in shape-constrained estimation where the goal is to estimate an unknown nondecreasing regression function f from independent pairs (x_i,y_i) where 𝔼[y_i]=f(x_i), i=1,...n. While this problem is well understood both statistically and computationally, much less is known about its uncoupled counterpart where one is given only the unordered sets {x_1,...,x_n} and {y_1,...,y_n}. In this work, we leverage tools from optimal transport theory to derive minimax rates under weak moments conditions on y_i and to give an efficient algorithm achieving optimal rates. Both upper and lower bounds employ moment-matching arguments that are also pertinent to learning mixtures of distributions and deconvolution.

Date and Time: 
Friday, October 26, 2018 - 1:15pm
Venue: 
Packard 202

IT-Forum: Arbitrarily Varying Broadcast and Relay Channels

Topic: 
Arbitrarily Varying Broadcast and Relay Channels
Abstract / Description: 

Two models of an arbitrarily varying channel (AVC) are studied; both are relevant to modern networks under jamming attacks by an adversary or a hacker. The arbitrarily varying broadcast channel is considered when state information is available at the transmitter in a causal manner. Inner and outer bounds are established, on both the random code capacity region and the deterministic code capacity region with degraded message sets. The form of the bounds raises the question whether the minimax theorem can be generalized to rate regions, i.e. whether the order of the intersection over state distributions and the union over Shannon strategies can be interchanged. A sufficient condition is given, under which this assertion holds and the random code capacity region is determined. As an example, the arbitrarily varying binary symmetric broadcast channel is examined, showing that there are cases where the condition holds, hence the capacity region is determined, and other cases where there is a gap between the bounds. The gap implies that the minimax theorem does not always hold for rate regions.

In the second part of the talk, a new model is introduced, namely, the arbitrarily varying relay channel. The results include the cutset bound, decode-forward bound and partial decode-forward bound on the random code capacity, which require modification of the usual methods for the AVC to fit the block Markov coding scheme. The random code capacity is further determined for special cases. Then, deterministic coding schemes are considered, and the deterministic code capacity is derived under certain conditions, for the degraded and reversely degraded relay channel, and the case of orthogonal sender components. The following question is addressed: If the encoder-decoder and encoder-relay marginals are both symmetrizable, does that necessarily imply zero capacity? We show and explain why the answer is no. The random code capacity is determined for the arbitrarily varying Gaussian relay channel with sender frequency division, and the deterministic code capacity is bounded using the techniques of Csisz\'ar and Narayan's 1991 paper on the Gaussian AVC. It is observed that the gap vanishes as the input becomes less constrained. It is commonly believed that the primitive relay channel "captures most essential features and challenges of relaying, and thus serves as a good testbed for new relay coding techniques" (Kim, 2007). It is observed that in the arbitrarily varying case, this may no longer be true.

This work is part of a Ph.D. thesis under the supervision of Yossef Steinberg.

Date and Time: 
Friday, October 12, 2018 - 1:15pm
Venue: 
Packard 202

IT-Forum: Structured Cooperation for Channels with Feedback and beyond

Topic: 
Structured Cooperation for Channels with Feedback and beyond
Abstract / Description: 

The capacities of fundamental communication problems such as channels with feedback and two-way communications channels are characterized with multi-letter expressions. The challenge in simplifying these expressions is their exhaustive dependence on all information that is accumulated throughout the communication. In this talk, we aim to simplify such capacities by imposing a structure on the accumulated data via a new sequential quantization technique on a directed graph.

First application of this method is for channels with memory and feedback. We will show upper and lower single-letter bounds on the capacity. The bounds are expressed with structured auxiliary random variable (r.v.), a notion that suits problems of sequential nature. For all cases where the capacity is known, the bounds are tight (with small cardinality of the structured auxiliary r.v.). This reveals a simple capacity formula that captures the major role of structure in feedback problems. We will also present a simple and sequential coding scheme, which is based on the posterior matching principle, and achieves the lower bound (and the capacity in many cases).

As time permits, we will show that structure is beneficial for other communication scenarios such as two-way communication channels with common outputs and the energy harvesting model.

The talk is based on a joint work with Prof. Henry Pfister (Duke Univeristy), Prof. Haim Permuter (BGU) and Prof. Navin Kashyap (IISc).

Date and Time: 
Monday, October 8, 2018 - 4:15pm
Venue: 
Packard 202

IT-Forum: Data-Driven Policy Learning: Generalization and Optimization

Topic: 
Data-Driven Policy Learning: Generalization and Optimization
Abstract / Description: 

The problem of learning good treatment assignment rules from observational data lies at the heart of many challenges in data-driven decision making. While there is a growing body of literature devoted to this problem, most existing results are focused on the binary-action case (i.e., where one action corresponds to assignment to control and to assignment to treatment). In this paper, we study the offline multi-action policy learning problem with observational data and, building on the theory of efficient semi-parametric inference, propose and implement a policy learning algorithm that achieves asymptotically minimax-optimal regret. To the best of our knowledge, this is the first result of this type in the multi-action setup and provides a substantial performance improvement over the existing learning algorithms. We additionally investigate the application aspects of policy learning by working with decision trees, and discuss two different approaches for solving the key step of the learning algorithm to exact optimality, one using a mixed integer program formulation and the other using a tree-search based algorithm.

This is joint work with Susan Athey and Stefan Wager.


 

The Information Theory Forum (IT-Forum) at Stanford ISL is an interdisciplinary academic forum which focuses on mathematical aspects of information processing. With a primary emphasis on information theory, we also welcome researchers from signal processing, learning and statistical inference, control and optimization to deliver talks at our forum. We also warmly welcome industrial affiliates in the above fields. The forum is typically held in Packard 202 every Friday at 1:15 pm during the academic year.

The Information Theory Forum is organized by graduate students Yanjun Han and Yihui Quek. To suggest speakers, please contact any of the students.

Date and Time: 
Friday, October 5, 2018 - 1:15pm
Venue: 
Packard 202

IT-Forum presents Representations, fairness, and privacy: information-theoretic tools for machine learning

Topic: 
Representations, fairness, and privacy: information-theoretic tools for machine learning
Abstract / Description: 

Information theory can shed light on the algorithm-independent limits of learning from data and serve as a design driver for new machine learning algorithms. In this talk, we discuss a set of flexible information-theoretic tools called the principal inertia components (PICs) that can be used to (i) understand fairness and discrimination in machine learning models, (ii) provide an estimation-theoretic view of privacy, and (iii) characterize data representations learned by complex learning models. The PICs enjoy a long history in both the statistics and information theory, and provide a fine-grained decomposition of the dependence between two random variables. We illustrate these techniques in both synthetic and real-world datasets, and discuss future research directions.

Date and Time: 
Friday, September 28, 2018 - 1:15pm
Venue: 
Packard 202

IT-Forum: Reverse hypercontractivity beats measure concentration for information theoretic converses

Topic: 
Reverse hypercontractivity beats measure concentration for information theoretic converses
Abstract / Description: 

Concentration of measure is a collection of tools and results from analysis and probability theory that have been used in many areas of pure and applied mathematics. Arguably, the first data science application of measure concentration (under the name ''blowing-up lemma'') is the proof of strong converses in multiuser information theory by Ahlswede, G\'acs and K\"orner in 1976. Since then, measure concentration has found applications in many other information theoretic problems, most notably the converse (impossibility) results in information theory. Motivated by this, information theorists (e.g. Marton) have also contributed to the mathematical foundations of measure concentration using their information-theoretic techniques.

Now, after all the past 40 years of such progress, we found that, amusingly, measure concentration is not the right hammer for many of these information theoretic applications. We introduce a new machinery based on functional inequalities and reverse hypercontractivity which yields strict improvements in terms of sharpness of the bounds, generality of the source/channel distributions, and simplicity of the proofs. Examples covered in the talk include: 1. optimal second-order converse to common randomness generation with rate-limited communication; 2. sharpening the relay channel converse bounds by and Wu and Ozgur with much simpler proofs.

The work benefited from collaborations with Thomas Courtade, Paul Cuff, Ayfer Ozgur, Ramon van Handel, and Sergio Verd\'u.

Date and Time: 
Friday, August 24, 2018 - 1:15pm
Venue: 
Packard 202

IT-Forum: Hardware-limited task-based quantization

Topic: 
Hardware-limited task-based quantization
Abstract / Description: 

Quantization plays a critical role in digital signal processing systems. Quantizers are typically designed to obtain an accurate digital representation of the input signal, operating independently of the system task, and are commonly implemented using serial scalar analog-to-digital converters (ADCs). This talk is concerned with hardware-limited task-based quantization, where a system utilizing a serial scalar ADC is designed to provide a suitable representation in order to allow the recovery of a parameter vector underlying the input signal. We propose hardware-limited task-based quantization systems for a fixed and finite quantization resolution, and characterize their achievable distortion. Our results illustrate the benefits of properly taking into account the underlying task in the design of the quantization scheme.

Date and Time: 
Wednesday, June 13, 2018 - 1:15pm
Venue: 
Packard 202

Pages

Optics and Electronics Seminar

Optics & Electronics Seminar presents New designer materials: Sculpting electromagnetic fields on the atomic scale

Topic: 
New designer materials: Sculpting electromagnetic fields on the atomic scale
Abstract / Description: 

New optical nanomaterials hold the potential for breakthroughs in a wide range of areas from ultrafast optoelectronics such as modulators, light sources and hyperspectral detectors, to efficient upconversion for energy applications, bio-sensing and on-chip components for quantum information science. An exciting opportunity to realize such new nanomaterials lies in controlling the local electromagnetic environment on the atomic- and molecular-scale, (~1-10 nm) which enables extreme local field enhancements. We use creative nanofabrication techniques at the interface between chemistry and physics to realize this new regime, together with advanced, ultrafast optical techniques to probe the emerging phenomena. Here, I will provide an overview of our recent research including high-speed thermal photodetectors, ultrafast spontaneous emission and enhanced biosensors.

Date and Time: 
Monday, November 26, 2018 - 4:15pm
Venue: 
Spilker 232

Detecting Single Photons with Superconductors

Topic: 
Detecting Single Photons with Superconductors
Abstract / Description: 

From space communications to quantum communications to sensing dark matter, ultrasenstive, ultrafast photodetectors are required. But conventional detector technologies often fall short, exhibiting noise, slow response times, poor sensitivity, or a combination of these issues. In contrast, superconducting detectors based on nanowires provide a unique combination of high speed, excellent efficiency, and low noise. Their underlying physical operating mechanism also provides a rich parameter space for application of physics across the optical, condensed-matter, and microwave domains. For example, we have recently used an ultra-slow plasmonic microwave mode in the nanowires to demonstrate single-photon-sensitive imaging. This rich physical parameter space for engineering has has resulted in improved device performance and extended the impact of these devices even further.

Date and Time: 
Tuesday, November 27, 2018 - 4:15pm
Venue: 
Packard 101

OSA/SPIE Seminar presents Photovoltaic Restoration of Sight in Retinal Degeneration

Topic: 
Photovoltaic Restoration of Sight in Retinal Degeneration
Abstract / Description: 

Retinal degenerative diseases lead to blindness due to loss of the "image capturing" photoreceptors, while neurons in the "image-processing" inner retinal layers are relatively well preserved. Information can be reintroduced into the visual system using electrical stimulation of the surviving inner retinal neurons. Some electronic retinal prosthetic systems have been already approved for clinical use, but they provide low resolution and involve very difficult implantation procedures.

We developed a photovoltaic subretinal prosthesis which converts light into pulsed electric current, stimulating the nearby inner retinal neurons. Visual information is projected onto the retina from video goggles using pulsed nearinfrared (~880nm) light. This design avoids the use of bulky electronics and wiring, thereby greatly reducing the surgical complexity. Optical activation of the photovoltaic pixels allows scaling the implants to thousands of electrodes. In preclinical studies, we found that prosthetic vision with subretinal implants preserves many features of natural vision, including flicker fusion at high frequencies (>20 Hz), adaptation to static images, center-surround organization and non-linear summation of subunits in receptive fields, providing high spatial resolution. Results of the clinical trial with our implants (PRIMA, Pixium Vision) having 100µm pixels, as well as preclinical measurements with 75 and 55µm pixels, confirm that spatial resolution of prosthetic vision can reach the sampling density limit.

For a broad acceptance of this technology by patients who lost central vision due to age-related macular degeneration, visual acuity should exceed 20/100, which requires pixels smaller than 25µm. I will describe the fundamental limitations in electro-neural interfaces and 3-dimensional configurations which should enable such a high spatial resolution. Ease of implantation of these wireless arrays, combined with high resolution opens the door to highly functional restoration of sight.

Date and Time: 
Thursday, November 15, 2018 - 3:45pm
Venue: 
Shriram 262

AP483, Ginzton Lab, & AMO Seminar Series presents Impact of Structural Correlation and Monomer Heterogeneity in the Phase Behavior of Soft Materials and Chromosomal DNA

Topic: 
Impact of Structural Correlation and Monomer Heterogeneity in the Phase Behavior of Soft Materials and Chromosomal DNA
Abstract / Description: 

Polymer self-assembly plays a critical role in a range of soft-material applications and in the organization of chromosomal DNA in living cells. In many cases, the polymer chains are composed of incompatible monomers that are not regularly arranged along the chains. The resulting phase segregation exhibits considerable heterogeneity in the microstructures, and the size scale of these morphologies can be comparable to the statistical correlation that arises from the molecular rigidity of the polymer chains. To establish a predictive understanding of these effects, molecular models must retain sufficient detail to capture molecular elasticity and sequence heterogeneity. This talk highlights efforts to capture these effects using analytical theory and computational modeling. First, we demonstrate the impact of structural rigidity on the phase segregation of copolymer chain in the melt phase, resulting in non-universal phase phenomena due to the interplay of concentration fluctuations and structural correlation. We then demonstrate how these effects impact the phase behavior in statistical random copolymers and in heterogeneous copolymers based on chromosomal DNA properties. With these results, we demonstrate that the spatial segregation of DNA in living cells can be predicted using a heterogeneous copolymer model of microphase segregation.

Date and Time: 
Monday, November 5, 2018 - 4:15pm
Venue: 
Spilker 232

OSA/SPIE Seminar: Entanglement across disciplines

Topic: 
Entanglement across disciplines
Abstract / Description: 

As physicists or engineers we may be aware that philosophers and historians have long been interested in quantum theory and its potential ontological implications. Over the past few decades, diverse new branches of the humanities and social sciences have begun to grapple with aspects of quantum physics and to offer radical interpretive approaches. In this talk I'll briefly introduce some of these developments and then invite the audience to participate in an open discussion. The presentation will be non-technical in nature but I'll assume that everyone is familiar with the structure and application of quantum theory.

Date and Time: 
Wednesday, October 31, 2018 - 4:00pm
Venue: 
Spilker 232

AP483, Ginzton Lab, & AMO Seminar Series presents "Quantum Electrodynamics of Superconducting Circuits"

Topic: 
Quantum Electrodynamics of Superconducting Circuits
Abstract / Description: 

The demand for rapid and high-fidelity execution of initialization, gate and read-out operations casts tight constraints on the accuracy of quantum electrodynamic modeling of superconducting integrated circuits. Attaining the required accuracies requires reconsidering our basic approach to the quantization of the electromagnetic field in a light-confining medium and the notion of normal modes. I will discuss a computational framework based on the Heisenberg-Langevin approach to address these fundamental questions. This framework allows the accurate determination of the quantum dynamics of a superconducting qubit in an arbitrarily complex electromagnetic environment, free of divergences that have plagued earlier approaches. I will also discuss the effectiveness of this computational approach in meeting the demands of present-day quantum computing research.


Academic year 2018-2019, please join us at Spilker room 232 every Monday afternoon from 4 pm for the AP 483 & Ginzton Lab, and AMO Seminar Series.

Refreshments begin at 4 pm, seminar at 4:15 pm.

Date and Time: 
Monday, December 3, 2018 - 4:15pm
Venue: 
Spilker 232

AP483, Ginzton Lab, & AMO Seminar Series

Topic: 
When quantum-information scrambling met quasiprobabilities
Abstract / Description: 

We do physics partially out of a drive to understand essences. One topic whose essence merits understanding is the out-of-time-ordered correlator (OTOC). The OTOC reflects quantum manybody thermalization, chaos, and scrambling (the spread of quantum information through manybody entanglement). The OTOC, I will show, equals an average over a quasiprobability distribution. A quasiprobability resembles a probability but can become negative and nonreal. Such nonclassical values can signal nonclassical physics. The OTOC quasiprobability has several applications: Experimentally, the quasiprobability points to a scheme for measuring the OTOC (via weak measurements, which refrain from disturbing the measured system much). The quasiprobability also signals false positives in attempts to measure scrambling of open systems. Theoretically, the quasiprobability links the OTOC to uncertainty relations, to nonequilibrium statistical mechanics, and more strongly to chaos. As coarse-graining the quasiprobability yields the OTOC, the quasiprobability forms the OTOC's essence.

References
• NYH, Phys. Rev. A 95, 012120 (2017). https://journals.aps.org/pra/abstract/10.1103/PhysRevA.95.012120
• NYH, Swingle, and Dressel, Phys. Rev. A 97, 042105 (2018). https://journals.aps.org/pra/abstract/10.1103/PhysRevA.97.042105
• NYH, Bartolotta, and Pollack, arXiv:1806.04147 (2018). https://arxiv.org/abs/1806.04147
• Gonzàlez Alonso, NYH, and Dressel, arXiv:1806.09637 (2018). https://arxiv.org/abs/1806.09637
• Swingle and NYH, Phys. Rev. A 97, 062113 (2018). https://journals.aps.org/pra/abstract/10.1103/PhysRevA.97.062113
• Dressel, Gonzàlez Alonso, Waegell, and NYH, Phys. Rev. A 98, 012132 (2018). https://journals.aps.org/pra/abstract/10.1103/PhysRevA.98.012132


Academic year 2018-2019, please join us at Spilker room 232 every Monday afternoon from 4 pm for the AP 483 & Ginzton Lab, and AMO Seminar Series.

Refreshments begin at 4 pm, seminar at 4:15 pm.

Date and Time: 
Monday, November 12, 2018 - 4:15pm
Venue: 
Spilker 232

AP483, Ginzton Lab, & AMO Seminar Series presents Conductivity of a perfect crystal

Topic: 
Conductivity of a perfect crystal
Abstract / Description: 

Dissipation of electrical current in typical metals is due to scattering off material defects and phonons. But what if the material were a perfect crystal, and sufficiently stiff or cold to eliminate phonons -- would conductivity become infinite? We realize an analogous scenario with atomic fermions in a cubic optical lattice, and measure conductivity. The equivalent of Ohm's law for neutral particles gives conductivity as the ratio of particle current to the strength of an applied force. Our measurements are at non-zero frequency (since a trapping potential prevents dc current flow), giving the low-frequency spectrum of real and imaginary conductivity. Since our atoms carry no charge, we measure particle currents with in-situ microscopy, with which both on- and off-diagonal response is visible. Sum rules are used to relate the observed conductivity to thermodynamic properties such as kinetic energy. We explore the effect of lattice depth, temperature, interaction strength, and atom number on conductivity. Using a relaxation-time approximation, we extract the transport time, i.e., the relaxation rate of current through collisions. Returning to the initial question, we demonstrate that fermion-fermion collisions damp current since the lattice breaks Galilean invariance.


Academic year 2018-2019, please join us at Spilker room 232 every Monday afternoon from 4 pm for the AP 483 & Ginzton Lab, and AMO Seminar Series.

Refreshments begin at 4 pm, seminar at 4:15 pm.

Date and Time: 
Monday, October 29, 2018 - 4:15pm
Venue: 
Spilker 232

AP483, Ginzton Lab, & AMO Seminar Series

Topic: 
New opportunities with old photonic materials
Abstract / Description: 

 Lithium niobate (LN) is an "old" material with many applications in optical and microwave technologies, owing to its unique properties that include large second order nonlinear susceptibility, large piezoelectric response, and wide optical transparency window. Conventional LN components, including modulators and periodically polled frequency converters, have been the workhorse of the optoelectronic industry. They are reaching their limits, however, as they rely on weakly guiding ion-diffusion defined optical waveguides in bulk LN crystal. I will discuss our efforts aimed at the development of integrated LN platform, featuring sub-wavelength scale light confinement and dense integration of optical and electrical components, that has the potential to revolutionize optical communication networks and microwave photonic systems, as well as enable realization of quantum photonic circuits. Good example is our recently demonstrated integrated LN electro-optic modulator that can be driven directly by a CMOS circuit, that supports data rates > 200 gigabits per second with > 90% optical transmission efficiency. I will also discuss our work on ultra-high Q LN optical cavities (Q ~ 10,000,000) and their applications, as well as nonlinear wavelength conversion using different approaches based on LN films.
Diamond is another "old" material with remarkable properties! It is transparent from the ultra-violet to infrared, has a high refractive index, strong optical nonlinearity and a wide variety of light-emitting defects of interest for quantum communication and computation. In my talk, I will summarize our efforts towards the development of integrated diamond quantum photonics platform aimed at realization of efficient photonic and phononic interfaces for diamond spin qubits.


 

Academic year 2018-2019, please join us at Spilker room 232 every Monday afternoon from 4 pm for the AP 483 & Ginzton Lab, and AMO Seminar Series.

Refreshments begin at 4 pm, seminar at 4:15 pm.

Date and Time: 
Monday, October 22, 2018 - 4:15pm
Venue: 
Spilker 232

Pages

SCIEN Talk

SCIEN Industry Affiliates Meeting

Topic: 
SCIEN Industry Affiliates Meeting
Abstract / Description: 

SCIEN Industry Affiliates Meeting gives you the opportunity to meet new SCIEN faculty and the postdocs and graduate students who are working in image systems engineering, with expertise in optics, computational imaging, human vision and machine learning. Read Poster Abstracts and bios.

Registration is required
Date and Time: 
Friday, November 30, 2018 - 1:30pm to 5:30pm
Venue: 
- please register -

SCIEN Talk: Plenoptic Medical Cameras

Topic: 
Plenoptic Medical Cameras
Abstract / Description: 

Optical imaging probes like otoscopes and laryngoscopes are essential tools used by doctors to see deep into the human body. Until now, they have been crucially limited to two-dimensional (2D) views of tissue lesions in vivo that frequently jeopardize their diagnostic usefulness. Depth imaging is critically needed in medical diagnostics because most tissue lesions manifest themselves as abnormal 3D structural changes. In this talk, I will talk our recent effort to develop three-dimensional (3D) plenoptic imaging tool that revolutionizes diagnosis with unprecedented sensitivity and specificity in the images produced. Particularly, I will discuss two plenoptic medical cameras, a plenoptic otoscope and a plenoptic laryngoscope, and their applications for in-vivo imaging.

Date and Time: 
Wednesday, December 5, 2018 - 4:30pm
Venue: 
Packard 101

SCIEN Talk: Perceptual Modeling with Multimodal Sensing

Topic: 
Perceptual Modeling with Multimodal Sensing
Abstract / Description: 

The research of human perception has enabled many visual applications in computer graphics that efficiently utilize computation resources to deliver a high quality experience within the limitations of the hardware. Beyond vision, humans perceive their surrounding using variety of senses to build a mental model of the world and act upon it. This mental image is often incomplete or incorrect which may have safety implications. As we cannot directly see inside the head, we need to read indirect signals projected outside. In the first part of the talk I will show how perceptual modeling can be used to overcome and exploit limitations of one specific human sense - the vision. Then, I will describe how we can build sensors to observe other human interactions connected first with physical touch and then with eye gaze patterns. Finally, I will outline how such readings can be used to teach computers to understand human behavior, to predict and to provide assistance or safety.

Date and Time: 
Wednesday, November 28, 2018 - 4:30pm
Venue: 
Packard 101

SCIEN Talk: Photo Forensics from JPEG Coding Artifacts

Topic: 
Photo Forensics from JPEG Coding Artifacts
Abstract / Description: 

The past few years have seen a startling and troubling rise in the fake-news phenomena in which everyone from individuals to state-sponsored entities produce and distribute mis-information, which is then widely promoted and disseminated on social media. The implications of fake news range from a mis-informed public to an existential threat to democracy, and horrific violence. At the same time, recent and rapid advances in machine learning are making it easier than ever to create sophisticated and compelling fake images and videos, making the fake-news phenomena even more powerful and dangerous. I will start by providing a broad overview of the field of image and video forensics and then I will describe in detail a suite of image forensic techniques that explicitly detect inconsistencies in JPEG coding artifacts.

Date and Time: 
Wednesday, November 14, 2018 - 4:30pm
Venue: 
Packard 101

SCIEN Talk presents Computational Single-Photon Imaging

Topic: 
Computational Single-Photon Imaging
Abstract / Description: 

[please note: this week's speaker has changed] Time-of-flight imaging and LIDAR systems enable 3D scene acquisition at long range using active illumination. This is useful for autonomous driving, robotic vision, human-computer interaction and many other applications. The technological requirements on these imaging systems are extreme: individual photon events need to be recorded and time-stamped at a picosecond timescale, which is facilitated by emerging single-photon detectors. In this talk, we discuss a new class of computational cameras based on single-photon detectors. These enable efficient ways for non-line-of-sight imaging (i.e., looking around corners) and efficient depth sensing as well as other unprecedented imaging modalities.

Date and Time: 
Wednesday, November 7, 2018 - 4:30pm
Venue: 
Packard 101

SCIEN Talk: Wavefront coding techniques and resolution limits for light field microscopy

Topic: 
Wavefront coding techniques and resolution limits for light field microscopy
Abstract / Description: 

Light field microscopy is a rapid, scan-less volume imaging technique that requires only a standard wide field fluorescence microscope and a microlens array. Unlike scanning microscopes, which collect volumetric information over time, the light field microscope captures volumes synchronously in a single photographic exposure, and at speeds limited only by the frame rate of the image sensor. This is made possible by the microlens array, which focuses light onto the camera sensor so that each position in the volume is mapped onto the sensor as a unique light intensity pattern. These intensity patterns are the position-dependent point response functions of the light field microscope. With prior knowledge of these point response functions, it is possible to "decode" 3-D information from a raw light field image and computationally reconstruct a full volume. In this talk I present an optical model for light field microscopy based on wave optics that accurately models light field point response functions. I describe an algorithm that solves for volumes using a GPU-accelerated iterative algorithm, and discuss priors that are useful for reconstructing biological specimens. I then explore the diffraction limit that applies for light field microscopy, and how it gives rise to a position-dependent resolution limits for this microscope. I'll explain how these limits differ from more familiar resolution metrics commonly used in 3-D scanning microscopy, like the Rayleigh limit and the optical transfer function (OTF). Using this theory of resolution limits for the light field microscope, I explore new wavefront coding techniques that can modify the light field resolution limits and can address certain common reconstruction artifacts, at least to a degree. Certain resolution trade-offs exist that suggest that light field microscopy is just one of potentially many useful forms of computational microscopy. Finally, I describe our application of light field microscopy in neuroscience where we have used it to record calcium activity in populations of neurons within the brains of awake, behaving animals.

Date and Time: 
Wednesday, October 31, 2018 - 4:30pm
Venue: 
Packard 101

SCIEN Talk: Is it real? Deep Neural Face Reconstruction and Rendering

Topic: 
Is it real? Deep Neural Face Reconstruction and Rendering
Abstract / Description: 

A broad range of applications in visual effects, computer animation, autonomous driving, and man-machine interaction heavily depend on robust and fast algorithms to obtain high-quality reconstructions of our physical world in terms of geometry, motion, reflectance, and illumination. Especially, with the increasing popularity of virtual, augmented and mixed reality devices, there comes a rising demand for real-time and low-latency solutions.

This talk covers data-parallel optimization and state-of-the-art machine learning techniques to tackle the underlying 3D and 4D reconstruction problems based on novel mathematical models and fast algorithms. The particular focus of this talk is on self-supervised face reconstruction from a collection of unlabeled in-the-wild images. The proposed approach can be trained end-to-end without dense annotations by fusing a convolutional encoder with a differentiable expert-designed renderer and a self-supervised training loss.

The resulting reconstructions are the foundation for advanced video editing effects, such as photo-realistic re-animation of portrait videos. The core of the proposed approach is a generative rendering-to-video translation network that takes computer graphics renderings as input and generates photo-realistic modified target videos that mimic the source content. With the ability to freely control the underlying parametric face model, we are able to demonstrate a large variety of video rewrite applications. For instance, we can reenact the full head using interactive user-controlled editing and realize high-fidelity visual dubbing.

Date and Time: 
Wednesday, October 24, 2018 - 4:30pm
Venue: 
Packard 101

SCIEN Talk: Computational microscopy of dynamic order across biological scales

Topic: 
Computational microscopy of dynamic order across biological scales
Abstract / Description: 

Living systems are characterized by emergent behavior of ordered components. Imaging technologies that reveal dynamic arrangement of organelles in a cell and of cells in a tissue are needed to understand the emergent behavior of living systems. I will present an overview of challenges in imaging dynamic order at the scales of cells and tissue, and discuss advances in computational label-free microscopy to overcome these challenges.

 

Date and Time: 
Wednesday, October 17, 2018 - 4:30pm
Venue: 
Packard 101

SCIEN Talk: How to train neural networks on LiDAR point clouds

Topic: 
How to train neural networks on LiDAR point clouds
Abstract / Description: 

Accurate LiDAR classification and segmentation is required for developing critical ADAS & Autonomous Vehicles components. Mainly, its required for high definition mapping and developing perception and path/motion planning algorithms. This talk will cover best practices for how to accurately annotate and benchmark your AV/ADAS models against LiDAR point cloud ground truth training data.

 

Date and Time: 
Wednesday, October 10, 2018 - 4:30pm
Venue: 
Packard 101

SCIEN & EE 292E: The challenge of large-scale brain imaging

Topic: 
The challenge of large-scale brain imaging
Abstract / Description: 

Advanced optical microscopy techniques have enabled the recording and stimulation of large populations of neurons deep within living, intact animal brains. I will present a broad overview of these techniques, and discuss challenges that still remain in performing large-scale imaging with high spatio-temporal resolution, along with various strategies that are being adopted to address these challenges.

Date and Time: 
Wednesday, October 3, 2018 - 4:30pm
Venue: 
Packard 101

Pages

SmartGrid

SmartGrid Seminar presents "Electricity Network Design and Operation in an Era of Solar and Storage"

Topic: 
Electricity Network Design and Operation in an Era of Solar and Storage
Abstract / Description: 

As prices for solar photovoltaics and battery energy storage plummet, grids around the globe are undergoing tremendous changes. How should we design and operate grids in the future in the presence of these technologies? This talk will cover some of my group's recent efforts to answer this question, focusing on a new approach to decentralized network optimization – a variant of the primal-dual subgradient method — that can be used to enable grid-integration of distributed energy resources such as solar photovoltaics, batteries and electric vehicles. I will then discuss how grids should be built in the future when distributed energy resource costs are so low. Using a simple concept called an iso-reliability curve, I will explain a method to identify cost-optimal fully decentralized systems – i.e. standalone solar home systems. After applying this method to a large solar resource dataset, I will present results indicating that in many unelectrified parts of the world, future decentralized systems will be able to deliver electricity at costs and reliabilities better than existing centralized grids.


The seminars are scheduled for 1:30 pm on the dates listed above. The speakers are renowned scholars or industry experts in power and energy systems. We believe they will bring novel insights and fruitful discussions to Stanford. This seminar is offered as a 1 unit seminar course, CEE 272T/EE292T. Interested students can take this seminar course for credit by completing a project based on the topics presented in this course.

 

Yours sincerely,
Smart Grid Seminar Organization Team,

Ram Rajagopal, Associate Professor, Civil & Environmental Engineering, and Electrical Engineering
Sila Kiliccote, Managing Director of Grid Innovations, Bits & Watts 
Chin-Woo Tan, Director, Stanford Smart Grid Lab 
Yuting Ji, Postdoctoral Scholar, Civil and Environmental Engineering

Date and Time: 
Thursday, December 6, 2018 - 1:30pm
Venue: 
Y2E2 111

SmartGrid Seminar: Battery storage

Topic: 
Battery storage: New Applications, Markets and Business Models
Abstract / Description: 

Since 2015, Tesla has installed a total of over one gigawatt-hour of energy storage that is critical for using renewable energy at scale. Over 20,000 customers across 40 countries are using Tesla stationary storage products for a variety of sustainable energy applications: powering filtration systems for clean water in Puerto Rico, stabilizing the grid in Australia, cooling classrooms in Hawaii, and powering entire islands in the South Pacific, etc. This talk will introduce the general efforts of Tesla's Energy Optimization Team, which develops the "brain" of its energy storage products. Optimization and machine learning techniques are utilized on all different products. A few recent projects will also be presented.


The seminars are scheduled for 1:30 pm on the dates listed above. The speakers are renowned scholars or industry experts in power and energy systems. We believe they will bring novel insights and fruitful discussions to Stanford. This seminar is offered as a 1 unit seminar course, CEE 272T/EE292T. Interested students can take this seminar course for credit by completing a project based on the topics presented in this course.

 

Yours sincerely,
Smart Grid Seminar Organization Team,

Ram Rajagopal, Associate Professor, Civil & Environmental Engineering, and Electrical Engineering
Sila Kiliccote, Managing Director of Grid Innovations, Bits & Watts 
Chin-Woo Tan, Director, Stanford Smart Grid Lab 
Yuting Ji, Postdoctoral Scholar, Civil and Environmental Engineering

Date and Time: 
Thursday, November 15, 2018 - 1:30pm
Venue: 
Y2E2 111

SmartGrid Seminar presents Power Electronics: A Key Enabling Technology for Smart Grid

Topic: 
Power Electronics: A Key Enabling Technology for Smart Grid
Abstract / Description: 

Power electronic converters impact all aspects of power systems – generation (renewable), transmission, distribution and end use. Power electronics is the key technology that enables reliable and secure integration of very large-scale renewable resources to the grid, new architectures including micro-grids, distributed grid control, and the rapid shift to electric transportation. This talk will highlight power electronics and controls in advanced PV inverters, wind energy systems, solid-state transformers and EV infrastructure. Key concepts that explain how the advanced functionalities are realized will be described. Recent advances in high voltage power electronics with wide bandgap devices, new topologies, and emerging trends and research challenges will be presented.


The seminars are scheduled for 1:30 pm on the dates listed above. The speakers are renowned scholars or industry experts in power and energy systems. We believe they will bring novel insights and fruitful discussions to Stanford. This seminar is offered as a 1 unit seminar course, CEE 272T/EE292T. Interested students can take this seminar course for credit by completing a project based on the topics presented in this course.

 

Yours sincerely,
Smart Grid Seminar Organization Team,

Ram Rajagopal, Associate Professor, Civil & Environmental Engineering, and Electrical Engineering
Sila Kiliccote, Managing Director of Grid Innovations, Bits & Watts
Chin-Woo Tan, Director, Stanford Smart Grid Lab
Yuting Ji, Postdoctoral Scholar, Civil and Environmental Engineering

Date and Time: 
Thursday, November 8, 2018 - 1:30pm
Venue: 
Y2E2 111

SmartGrid Seminar: Clean Energy at the Crossroads: A Look Ahead Through the Eyes of an Environmental Economist

Topic: 
Clean Energy at the Crossroads: A Look Ahead Through the Eyes of an Environmental Economist
Abstract / Description: 

California has the will, ambition, technology and legal requirement to decarbonize our energy sector by 2045. In the dozen years since passage of AB32, we have made great progress but we may be making some grave mistakes. In this discussion, Dr. Fine describes how distributed energy resources are presenting new opportunities in distribution resources, transmission and procurement planning, and market reforms that will determine if our clean energy future is one that is affordable for all.

Date and Time: 
Thursday, October 11, 2018 - 1:30pm
Venue: 
Y2E2 111

SmartGrid Seminar: Future Power System Control Functions: An Industry Perspective

Topic: 
Future Power System Control Functions: An Industry Perspective
Abstract / Description: 

This talk provides an overview of Siemens Corporate Technology's recent research on new control functions for future power systems. Three different topics are discussed: (a) adaptive power oscillation damping optimization to increase the stability reserve of power systems, (b) robust power flow optimization to increase power system resilience to volatile generation, and (c) new research challenges for autonomous microgrids that provide autonomous operation and plug-and-produce capabilities.

Date and Time: 
Thursday, May 31, 2018 - 1:30pm
Venue: 
Y2E2 111

SmartGrid Seminar: Trends in Electric Power Distribution System Analysis at PNNL

Topic: 
Trends in Electric Power Distribution System Analysis at PNNL
Abstract / Description: 

Pacific Northwest National Laboratory (PNNL) originated and continues to maintain one of the two leading open-source distribution system simulators, called GridLAB-D, which has been downloaded 80,000+ times world-wide. While it continues to improve core functionality, PNNL is placing more emphasis recently on GridLAB-D as part of a development platform, improving its interoperability and opening the software up to more customization by researchers. This talk will cover two ongoing open-source development projects, funded by the U. S. Department of Energy, that incorporate and extend GridLAB-D. One of these projects is also expected to contribute distribution feeder model conversion tools for a new California Energy Commission project headed by SLAC. Highlights of the talk will include:

  • Transactive energy simulation platform, at tesp.readthedocs.io/en/latest
  • GridAPPS-D application development platform, at gridappsd.readthedocs.io/en/latest
  • Evole GridLAB-D's co-simulation support from FNCS interface, to a multi-lab interface called HELICS compliant with Functional Mockup Interface (FMI): https://github.com/GMLC-TDC/HELICS-src
  • Leveraging new capabilities for large-building simulation in JModelica, power flow analysis in OpenDSS, and transactive energy system agents in Python
  • Implementation and use of the Common Information Model (CIM) in a NoSQL triple-store database for standardized feeder model conversion
  • Comparison of different types of stochastic modeling for load and distributed energy resource (DER) output variability, and its impact on feeder model order reduction and state estimation
  • Special system protection example concerns on urban secondary networks with high penetration of DER
Date and Time: 
Thursday, May 24, 2018 - 1:30pm
Venue: 
Y2E2 111

SmartGrid Seminar: Renewable Scenario Generation Using Adversarial Networks

Topic: 
Renewable Scenario Generation Using Adversarial Networks
Abstract / Description: 

Scenario generation is an important step in the operation and planning of power systems. In this talk, we present a data-driven approach for scenario generation using the popular generative adversarial networks, where to deep neural networks are used in tandem. Compared with existing methods that are often hard to scale or sample from, our method is easy to train, robust, and captures both spatial and temporal patterns in renewable generation. In addition, we show that different conditional information can be embedded in the framework. Because of the feedforward nature of the neural networks, scenarios can be generated extremely efficiently.

Date and Time: 
Thursday, April 19, 2018 - 1:30pm
Venue: 
Y2E2 111

SmartGrid Seminar: Increasing Power Grid Resiliency for Adverse Conditions & the Role of Renewable Energy Resources and Microgrids

Topic: 
Increasing Power Grid Resiliency for Adverse Conditions & the Role of Renewable Energy Resources and Microgrids
Abstract / Description: 

System resiliency is the number 1 concern for electrical utilities in 2018 according to the CEO of the PJM, the nation's largest independent system operator. This talk will offer insights and practical answers through examples, of how power grids can be affected by weather and how countermeasures, such microgrids, can be applied to mitigate them. It will focus on two major events; Super Storm Sandy and Hurricane Maria, and the role of renewable energy resources and microgrids in these two natural disasters. It will discuss the role of microgrids in blackstarting the power grid after a blackout.

Date and Time: 
Thursday, April 12, 2018 - 1:30pm
Venue: 
Y2E2 111

SmartGrid Seminar: Transmission-Distribution Coordinated Energy Management: A Solution to the Challenge of Distributed Energy Resource Integration

Topic: 
Transmission-Distribution Coordinated Energy Management: A Solution to the Challenge of Distributed Energy Resource Integration
Abstract / Description: 

Transmission-distribution coordinated energy management (TDCEM) is recognized as a promising solution to the challenge of high DER penetration, but lack of a distributed computation method that universally and effectively works for TDCEM. To bridge this gap, a generalized master-slave-splitting (G-MSS) method is proposed based on a general-purpose transmission-distribution coordination model (G-TDCM), enabling G-MSS to be applicable to most central functions of TDCEM. In G-MSS, a basic heterogeneous decomposition (HGD) algorithm is first derived from the heterogeneous decomposition of the coupling constraints in the KKT system regarding G-TDCM. Optimality and convergence properties of this algorithm are proved. Furthermore, a modified HGD algorithm is developed by utilizing subsystem's response function, resulting in faster convergence. The distributed G-MSS method is then demonstrated to successfully solve central functions of TDCEM including power flow, contingency analysis, voltage stability assessment, economic dispatch and optimal power flow. Severe issues of over-voltage and erroneous assessment of the system security that are caused by DERs are thus resolved by G-MSS with modest computation cost. A real-world demonstration project in China will be presented.

Date and Time: 
Thursday, April 5, 2018 - 1:30pm
Venue: 
Y2E2 111

SmartGrid Seminar: Johanna Mathieu

Topic: 
TBA
Abstract / Description: 

The speakers are renowned scholars or industry experts in power and energy systems. We believe they will bring novel insights and fruitful discussions to Stanford. This seminar is offered as a 1 unit seminar course, CEE 272T/EE292T. Interested students can take this seminar course for credit by completing a project based on the topics presented in this course.

Date and Time: 
Thursday, March 1, 2018 - 1:30pm
Venue: 
Y2E2 111

Pages

Stanford's NetSeminar

Claude E. Shannon's 100th Birthday

Topic: 
Centennial year of the 'Father of the Information Age'
Abstract / Description: 

From UCLA Shannon Centennial Celebration website:

Claude Shannon was an American mathematician, electrical engineer, and cryptographer known as "the father of information theory". Shannon founded information theory and is perhaps equally well known for founding both digital computer and digital circuit design theory. Shannon also laid the foundations of cryptography and did basic work on code breaking and secure telecommunications.

 

Events taking place around the world are listed at IEEE Information Theory Society.

Date and Time: 
Saturday, April 30, 2016 - 12:00pm
Venue: 
N/A

NetSeminar

Topic: 
BlindBox: Deep Packet Inspection over Encrypted Traffic
Abstract / Description: 

SIGCOMM 2015, Joint work with: Justine Sherry, Chang Lan, and Sylvia Ratnasamy

Many network middleboxes perform deep packet inspection (DPI), a set of useful tasks which examine packet payloads. These tasks include intrusion detection (IDS), exfiltration detection, and parental filtering. However, a long-standing issue is that once packets are sent over HTTPS, middleboxes can no longer accomplish their tasks because the payloads are encrypted. Hence, one is faced with the choice of only one of two desirable properties: the functionality of middleboxes and the privacy of encryption.

We propose BlindBox, the first system that simultaneously provides both of these properties. The approach of BlindBox is to perform the deep-packet inspection directly on the encrypted traffic. BlindBox realizes this approach through a new protocol and new encryption schemes. We demonstrate that BlindBox enables applications such as IDS, exfiltration detection and parental filtering, and supports real rulesets from both open-source and industrial DPI systems. We implemented BlindBox and showed that it is practical for settings with long-lived HTTPS connections. Moreover, its core encryption scheme is 3-6 orders of magnitude faster than existing relevant cryptographic schemes.

Date and Time: 
Wednesday, November 11, 2015 - 12:15pm to 1:30pm
Venue: 
Packard 202

NetSeminar

Topic: 
Precise localization and high throughput backscatter using WiFi signals
Abstract / Description: 

Indoor localization holds great promise to enable applications like location-based advertising, indoor navigation, inventory monitoring and management. SpotFi is an accurate indoor localization system that can be deployed on commodity WiFi infrastructure. SpotFi only uses information that is already exposed by WiFi chips and does not require any hardware or firmware changes, yet achieves the same accuracy as state-of-the-art localization systems.

We then talk about BackFi, a novel communication system that enables high throughput, long range communication between very low power backscatter IoT sensors and WiFi APs using ambient WiFi transmissions as the excitation signal. We show via prototypes and experiments that it is possible to achieve communication rates of up to 5 Mbps at a range of 1 m and 1 Mbps at a range of 5 meters. Such performance is an order to three orders of magnitude better than the best known prior WiFi backscatter system.

Date and Time: 
Thursday, October 15, 2015 - 12:15pm to 1:30pm
Venue: 
Gates 104

NetSeminar

Topic: 
BlindBox: Deep Packet Inspection over Encrypted Traffic
Abstract / Description: 

SIGCOMM 2015, Joint work with: Justine Sherry, Chang Lan, and Sylvia Ratnasamy

Many network middleboxes perform deep packet inspection (DPI), a set of useful tasks which examine packet payloads. These tasks include intrusion detection (IDS), exfiltration detection, and parental filtering. However, a long-standing issue is that once packets are sent over HTTPS, middleboxes can no longer accomplish their tasks because the payloads are encrypted. Hence, one is faced with the choice of only one of two desirable properties: the functionality of middleboxes and the privacy of encryption.

We propose BlindBox, the first system that simultaneously provides both of these properties. The approach of BlindBox is to perform the deep-packet inspection directly on the encrypted traffic. BlindBox realizes this approach through a new protocol and new encryption schemes. We demonstrate that BlindBox enables applications such as IDS, exfiltration detection and parental filtering, and supports real rulesets from both open-source and industrial DPI systems. We implemented BlindBox and showed that it is practical for settings with long-lived HTTPS connections. Moreover, its core encryption scheme is 3-6 orders of magnitude faster than existing relevant cryptographic schemes.

Date and Time: 
Wednesday, October 7, 2015 - 12:15pm to 1:30pm
Venue: 
AllenX Auditorium

Pages

Statistics and Probability Seminars

Statistics Seminar: Inference, Computation, and Visualization for Convex Clustering and Biclustering

Topic: 
Inference, Computation, and Visualization for Convex Clustering and Biclustering
Abstract / Description: 

Hierarchical clustering enjoys wide popularity because of its fast computation, ease of interpretation, and appealing visualizations via the dendogram and cluster heatmap. Recently, several have proposed and studied convex clustering and biclustering which, similar in spirit to hierarchical clustering, achieve cluster merges via convex fusion penalties. While these techniques enjoy superior statistical performance, they suffer from slower computation and are not generally conducive to representation as a dendogram. In the first part of the talk, we present new convex (bi)clustering methods and fast algorithms that inherit all of the advantages of hierarchical clustering. Specifically, we develop a new fast approximation and variation of the convex (bi)clustering solution path that can be represented as a dendogram or cluster heatmap. Also, as one tuning parameter indexes the sequence of convex (bi)clustering solutions, we can use these to develop interactive and dynamic visualization strategies that allow one to watch data form groups as the tuning parameter varies. In the second part of this talk, we consider how to conduct inference for convex clustering solutions that addresses questions like: Are there clusters in my data set? Or, should two clusters be merged into one? To achieve this, we develop a new geometric representation of Hotelling's T2-test that allows us to use the selective inference paradigm to test multivariate hypotheses for the first time. We can use this approach to test hypotheses and calculate confidence ellipsoids on the cluster means resulting from convex clustering. We apply these techniques to examples from text mining and cancer genomics.

This is joint work with John Nagorski and Frederick Campbell.


The Statistics Seminars for Winter Quarter will be held in Room 380Y of the Sloan Mathematics Center in the Main Quad at 4:30pm on Tuesdays. 

Date and Time: 
Tuesday, March 13, 2018 - 4:30pm
Venue: 
Sloan Mathematics Building, Room 380Y

Statistics Seminar: Understanding rare events in models of statistical mechanics

Topic: 
Understanding rare events in models of statistical mechanics
Abstract / Description: 

Statistical mechanics models are ubiquitous at the interface of probability theory, information theory, and inference problems in high dimensions. To develop a refined understanding of such models, one often needs to study not only typical fluctuation theory but also the realm of atypical events. In this talk, we will focus on sparse networks and polymer models on lattices. In particular we will consider the rare events that a sparse random network has an atypical number of certain local structures, and that a polymer in random media has atypical weight. The random geometry associated with typical instances of these rare events is an important topic of inquiry: this geometry can involve merely local structures, or more global ones. We will discuss recent solutions to certain longstanding questions and connections to stochastic block models, exponential random graphs, eigenvalues of random matrices, and fundamental growth models.

Date and Time: 
Tuesday, January 30, 2018 - 4:30pm
Venue: 
Sloan Mathematics Building, Room 380Y

New Directions in Management Science & Engineering: A Brief History of the Virtual Lab

Topic: 
New Directions in Management Science & Engineering: A Brief History of the Virtual Lab
Abstract / Description: 

Lab experiments have long played an important role in behavioral science, in part because they allow for carefully designed tests of theory, and in part because randomized assignment facilitates identification of causal effects. At the same time, lab experiments have traditionally suffered from numerous constraints (e.g. short duration, small-scale, unrepresentative subjects, simplistic design, etc.) that limit their external validity. In this talk I describe how the web in general—and crowdsourcing sites like Amazon's Mechanical Turk in particular—allow researchers to create "virtual labs" in which they can conduct behavioral experiments of a scale, duration, and realism that far exceed what is possible in physical labs. To illustrate, I describe some recent experiments that showcase the advantages of virtual labs, as well as some of the limitations. I then discuss how this relatively new experimental capability may unfold in the future, along with some implications for social and behavioral science.

Date and Time: 
Thursday, March 16, 2017 - 12:15pm
Venue: 
Packard 101

Statistics Seminar

Topic: 
Brownian Regularity for the Airy Line Ensemble
Abstract / Description: 

The Airy line ensemble is a positive-integer indexed ordered system of continuous random curves on the real line whose finite dimensional distributions are given by the multi-line Airy process. It is a natural object in the KPZ universality class: for example, its highest curve, the Airy2 process, describes after the subtraction of a parabola the limiting law of the scaled weight of a geodesic running from the origin to a variable point on an anti-diagonal line in such problems as Poissonian last passage percolation. The Airy line ensemble enjoys a simple and explicit spatial Markov property, the Brownian Gibbs property.


In this talk, I will discuss how this resampling property may be used to analyse the Airy line ensemble. Arising results include a close comparison between the ensemble's curves after affine shift and Brownian bridge. The Brownian Gibbs technique is also used to compute the value of a natural exponent describing the decay in probability for the existence of several near geodesics with common endpoints in Brownian last passage percolation, where the notion of "near" refers to a small deficit in scaled geodesic weight, with the parameter specifying this nearness tending to zero.

Date and Time: 
Monday, September 26, 2016 - 4:30pm
Venue: 
Sequoia Hall, room 200

Claude E. Shannon's 100th Birthday

Topic: 
Centennial year of the 'Father of the Information Age'
Abstract / Description: 

From UCLA Shannon Centennial Celebration website:

Claude Shannon was an American mathematician, electrical engineer, and cryptographer known as "the father of information theory". Shannon founded information theory and is perhaps equally well known for founding both digital computer and digital circuit design theory. Shannon also laid the foundations of cryptography and did basic work on code breaking and secure telecommunications.

 

Events taking place around the world are listed at IEEE Information Theory Society.

Date and Time: 
Saturday, April 30, 2016 - 12:00pm
Venue: 
N/A

Pages

SystemX

SystemX Seminar presents "Planning and Decision Making for Autonomous Spacecraft and Space Robots"

Topic: 
Planning and Decision Making for Autonomous Spacecraft and Space Robots
Abstract / Description: 

In this talk I will present planning and decision-making techniques for safely and efficiently maneuvering autonomous aerospace vehicles during proximity operations, manipulation tasks, and surface locomotion. I will first address the "spacecraft motion planning problem," by discussing its unique aspects and presenting recent results on planning under uncertainty via Monte Carlo sampling. I will then turn the discussion to higher-level decision making; in particular, I will discuss an axiomatic theory of risk and how one can leverage such a theory for a principled and tractable inclusion of risk-awareness in robotic decision making, in the context of Markov decision processes and reinforcement learning. Throughout the talk, I will highlight a variety of space-robotic applications my research group is contributing to (including the Mars 2020 and Hedgehog rovers, and the Astrobee free-flying robot), as well as applications to the automotive and UAV domains.

This work is in collaboration with NASA JPL, NASA Ames, NASA Goddard, and MIT.

Date and Time: 
Thursday, December 6, 2018 - 4:30pm
Venue: 
Huang 018

SystemX Seminar presents "Killer Robots: Why you will NOT be owning a self-driving car"

Topic: 
Killer Robots: Why you will NOT be owning a self-driving car
Abstract / Description: 

This talk will provide a general overview and several examples of powerful robots that can kill people – unintentionally. It will then focus on human-transporting vehicles (self-driving cars). There are numerous significant limitations that will restrict your ability to own a self-driving car. Some of these limitations will be discussed in detail. The areas of discussion will include dynamics, customer needs, failure modes, and legal concerns.

Date and Time: 
Thursday, November 29, 2018 - 5:00pm
Venue: 
Huang 018

SystemX Seminar presents "Safe Control and Algorithmic Human-Robot Interaction"

Topic: 
Safe Control and Algorithmic Human-Robot Interaction
Abstract / Description: 

Dorsa Sadigh is an Assistant Professor in CS and EE.

Her work is focused on the design of algorithms for autonomous systems that safely and reliably interact with people.

Date and Time: 
Thursday, November 29, 2018 - 4:00pm
Venue: 
Huang 018

SystemX Seminar presents Beyond the hardware: Why you should launch a brand, not just a product

Topic: 
Beyond the hardware: Why you should launch a brand, not just a product
Abstract / Description: 

In the race to launch a product, the concept of "brand" is often an afterthought. Truth is, building a brand is basic to product survival. Good branding communicates quality, credibility and value. It outlives product cycles and inspires customer loyalty. So, how is an effective brand crafted? Diving into a collection of case studies, this talk will explore why design is essential for thinking beyond the hardware to create a brand that fosters an emotional connection between person and product.

Date and Time: 
Thursday, November 8, 2018 - 4:30pm
Venue: 
Huang 018

SystemX Seminar BONUS LECTURE: New Mysteries vs Advanced Technology in Radio Astronomy

Topic: 
New Mysteries vs Advanced Technology in Radio Astronomy
Abstract / Description: 

1. New Mysteries

  • Fast Radio Bursts, FRB's – 1ms pulses, non‐recurring, which strike the earth at a rate of 5000 per day, and are of unknown orgin – more about this
  • Gravitational Waves – detected by LIGO but very coarse directions; need radio or optical observations to locate and understand the orgins
  • Recent Nature paper on 78 MHz dip in cosmic background ‐ needs confirmation and theoretical explanation

2. Transformational Radio Telescopes – The traditional need for large collecting area and sharp beamwidths needs to be supplemented by telescopes which can find transients from unknown directions in the sky,

  • Current example, all the sky, all the time – The Caltech long wavelength array
  • DSA, an array to locate and understand the orgins of FRB's
  • Next generation affordable array, 2000 x 5m telescopes.

3. Advanced RF Technology for Radio Astronomy and Quantum Computing

  • Ultra low noise without cryogenics – 1.4 GHz LNA with 12K noise
  • Development of wireless, solar powered, radio telescopes
  • LNA requirements for quantum computing – effects of self heating
Date and Time: 
Wednesday, November 7, 2018 - 2:00pm
Venue: 
Packard 202

SystemX Seminar presents Robot Reality Check

Topic: 
Robot Reality Check
Abstract / Description: 

Rich will provide an overview of the general status of the robotics industry and its impact in various market segments. He will also discuss his experiences in early stage robotics in Silicon Valley and review the landscape of emerging robotics companies. Finally, Rich will discuss his journey with Seismic and share insights on the company strategy and the new category of apparel called Powered Clothing.

Date and Time: 
Thursday, November 1, 2018 - 4:30pm
Venue: 
Huang 018

SystemX Seminar presents How to Build a Processor for Machine Learning

Topic: 
How to Build a Processor for Machine Learning
Abstract / Description: 

Compute, data, and algorithms have combined to power the recent huge strides in machine intelligence. But there is still plenty of scope for improvement, and hardware is finally coming to the fore. Machine intelligence is the future of computing, so what needs to happen at a hardware level to make it faster and more energy- and cost-efficient?

This talk will outline the key considerations in how to build an efficient processor for machine intelligence both for today's state of the art networks and also to more rapidly and more flexibly support future innovations in algorithms and model structures.

Date and Time: 
Tuesday, October 23, 2018 - 1:30pm
Venue: 
Gates B12

SystemX Seminar: BONUS LECTURE- Automatic Implementation of Secure SOC'

Topic: 
BONUS LECTURE Automatic Implementation of Secure SOC's
Abstract / Description: 

Need for incorporation of security into next generation of microelectronics, improved economics of the platform-based design and advances in high level synthesis make efficient implementation of secure, complex SoCs possible. An opportunity exists to consider new approaches, tools, methodologies and IP that enable semi-automated and automatic approaches to assembly and integration that substantially improve SoC security. One path forward may be to develop a technology where secure, configurable, extensible, application-specific platforms can be used in conjunction with synthesis technology to automatically incorporate original functionality derived from an implementation-independent executable models as either hardware or software. Program concept for addressing this challenge at DARPA will be presented.

Date and Time: 
Wednesday, October 17, 2018 - 3:00pm
Venue: 
Packard 202

EE380 Computer Systems Colloquium: Efficient and Resilient Systems in the Cognitive Era

Topic: 
Efficient and Resilient Systems in the Cognitive Era
Abstract / Description: 

A focus on energy efficiency in the late CMOS design era, requires extra careful attention to system reliability and resilience to hardware-sourced errors. At the same time, the emergence of AI (cognitive) applications as a key growth segment is quite obvious. This talk will attempt to address the special challenges that next generation AI (or cognitive) systems pose, with a particular focus on next generation cognitive IoT architectures. We will discuss this primarily from the point of view of providing energy-efficient resilience in environments that are likely to have built-in vulnerability to errors. Such uncertainty stems not just from potentially error-prone (late CMOS) hardware designed for extreme efficiency, but also from algorithmic brittleness of the most prevalent forms of machine learning/deep learning (ML/DL) solution strategies today. In that context, we will briefly examine the promise of the Adaptive Swarm Intelligence (ASI) architectural paradigm that we have recently started investigating at IBM Research. This is a form of distributed or decentralized computing applied to the world of mobile cognitive IoT, backed by resilient support from back-end cloud (server) systems. In addition to examining the promises of inherent system architectural scalability and in-field, continuous learning that ASI offers, we will argue (albeit philosophically!) about why this could open the door to new models of self-aware systems that mimic cooperative and conscious problem solving in a human setting.


The Stanford EE Computer Systems Colloquium (EE380) meets on Wednesdays 4:30-5:45 throughout the academic year. Talks are given before a live audience in Room B03 in the basement of the Gates Computer Science Building on the Stanford Campus. The live talks (and the videos hosted at Stanford and on YouTube) are open to the public.

Stanford students may enroll in EE380 to take the Colloquium as a one unit S/NC class. Enrolled students are required to keep and electronic notebook or journal and to write a short, pithy comment about each of the ten lectures and a short free form evaluation of the class in order to receive credit. Assignments are due at the end of the quarter, on the last day of examinations.

EE380 is a video class. Live attendance is encouraged but not required. We (the organizers) feel that watching the video is not a substitute for being present in the classroom. Questions are encouraged.

Many past EE380 talks are available on YouTube, see the EE380 Playlist.

Date and Time: 
Wednesday, October 3, 2018 - 4:30pm
Venue: 
Gates B03

Pages

Subscribe to RSS - Seminar / Colloquium