2017

Professor Gordon Wetzstein, left; postdoctoral research fellow Donald Dansereau (Image credit: L.A. Cicero)
July 2017

A new 4D camera designed by Professor Gordon Wetzstein and postdoc Dr. Donald Dansereau captures light field information over a 138° field of view.

The difference between looking through a normal camera and the new design is like the difference between looking through a peephole and a window, the scientists said.

"A 2D photo is like a peephole because you can't move your head around to gain more information about depth, translucency or light scattering," Dansereau said. "Looking through a window, you can move and, as a result, identify features like shape, transparency and shininess."

That additional information comes from a type of photography called light field photography, first described in 1996 by EE Professors Marc Levoy and Pat Hanrahan. Light field photography captures the same image as a conventional 2D camera plus information about the direction and distance of the light hitting the lens, creating what's known as a 4D image. A well-known feature of light field photography is that it allows users to refocus images after they are taken because the images include information about the light position and direction. Robots might use this to see through rain and other things that could obscure their vision.

The extremely wide field of view, which encompasses nearly a third of the circle around the camera, comes from a specially designed spherical lens. However, this lens also produced a significant hurdle: how to translate a spherical image onto a flat sensor. Previous approaches to solving this problem had been heavy and error prone, but combining the optics and fabrication expertise of UCSD and the signal processing and algorithmic expertise of Wetzstein's lab resulted in a digital solution to this problem that not only leads to the creation of these extra-wide images but enhances them.

This camera system's wide field of view, detailed depth information and potential compact size are all desirable features for imaging systems incorporated in wearables, robotics, autonomous vehicles and augmented and virtual reality.

"Many research groups are looking at what we can do with light fields but no one has great cameras. We have off-the-shelf cameras that are designed for consumer photography," said Dansereau. "This is the first example I know of a light field camera built specifically for robotics and augmented reality. I'm stoked to put it into peoples' hands and to see what they can do with it."

 

Two 138° light field panoramas and a depth estimate of the second panorama. (Image credit: Stanford Computational Imaging Lab and Photonic Systems Integration Laboratory at UC San Diego)

 


Read more at Professor Wetztein's research site, Stanford Computational Imaging Lab.

Excerpted from Stanford News, "New camera designed by Stanford researchers could improve robot vision and virtual reality," July 21, 2017.

Yuanfang Li and Dr. Ardavan Pedram: Best Paper Award, IEEE ASAP
July 2017

Co-authors Yuanfang Li (MS candidate) and Dr. Ardavan Pedram received the Best Paper Award at the 28th annual IEEE International Conference on Application-specific Systems, Architectures and Processors (ASAP).

The conference covers the theory and practice of application-specific systems, architectures and processors – specifically building upon traditional strengths in areas such as computer arithmetic, cryptography, compression, signal and image processing, network processing, reconfigurable computing, application-specific instruction-set processors, and hardware accelerators.

Yuanfang Li is an M.S. candidate and Dr. Ardavan Pedram is a senior research associate who manages the PRISM Project. The PRISM project enables the design of reconfigurable architectures to accelerate the building blocks of machine learning, high performance computing, and data science routines.

 

Congratulations to Yuanfang and Ardavan for their well-deserved award!

 

Abstract "CATERPILLAR: Coarse Grain Reconfigurable Architecture for Accelerating the Training of Deep Neural Networks":
Accelerating the inference of a trained DNN is a well studied subject. In this paper we switch the focus to the training of DNNs. The training phase is compute intensive, demands complicated data communication, and contains multiple levels of data dependencies and parallelism. This paper presents an algorithm/architecture space exploration of efficient accelerators to achieve better network convergence rates and higher energy efficiency for training DNNs. We further demonstrate that an architecture with hierarchical support for collective communication semantics provides flexibility in training various networks performing both stochastic and batched gradient descent based techniques. Our results suggest that smaller networks favor non-batched techniques while performance for larger networks is higher using batched operations.

June 2017

Congratulations to Dianmin Lin (PhD '16), she has been awarded the 2017 QEP Doctoral Research Prize, jointly with Dr. Jamie Francis-Jones (University of Bath).

The QEP Doctoral Research Prize recognizes students who have conducted work of an exceptional standard in the field of quantum electronics and photonics. The winning student receives an award of £250 and a certificate.

Dr. Dianmin Lin is recognized for the design and demonstration of all-dielectric (silicon) phase-gradient metasurface optical elements, such as axicons, flat lenses and blazed gratings, operating in transmission mode at visible wavelengths, as well as multifunctional metasurfaces providing new or combined functions that are difficult if not impossible to achieve with conventional optical components. Her research has been published in Advanced Materials, Nano Letters, and Science. Three patent applications have been filed for her work at Stanford, one patent has been issued, and two are pending.

Dianmin is currently a senior optical scientist working on augmented reality.

 

Congratulations to Dianmin on her well-deserved recognition and award!

The Brongersma Group

Pictured, The Brongersma Group is concerned with the development and understanding of nanophotonic devices. As part of a worldwide research and development effort on 'metamaterials' - manmade media that possess unique properties not found in nature, students in the group aim to nanostructure the layered materials in conventional optoelectronic devices so as to increase their performance or to achieve entirely new functions. They have successfully applied this approach to the fields of solar energy production, information technology, and optical imaging.

 

 

 

 

Excerpted from IOP's 'QEP Group Prize.'

June 2017

Professor David Tse has been appointed to the Thomas Kailath and Guanghan Xu Professorship in the School of Engineering. This professorship was established with an endowed gift from Guanghan Xu, a Stanford alum who earned his PhD in EE. Guanghan established this professorship to honor his advisor, Thomas Kailath, the Hitachi America Professor in the School of Engineering, Emeritus. The Thomas Kailath and Guanghan Xu Professorship carries preference for faculty whose academic focus is in the broad field of signal processing and its applications.

David has been a member of the Stanford faculty since 2014. His research focuses on information theory and its applications in various fields, including wireless communication, energy, and computational biology. David serves at the Stanford Information Systems Laboratory, and is the inventor of the proportional fair scheduling algorithm used in all third- and fourth-generation cellular systems. He also co-authored with Pramod Viswanath the text Fundamentals of Wireless Communication, which has been used in over 60 institutions around the world.

Prior to joining the Stanford faculty, David served in the department of electrical engineering and computer sciences at the University of California, Berkeley from 1995 to 2014, and was a member of the technical staff at AT&T Bell Laboratories from 1994 to 1995.

A fellow of the Institute of Electrical and Electronics Engineers (IEEE), David has received the IEEE Communications Society and Information Theory Society Joint Paper Award on three occasions, and he has served on the IEEE Information Theory Society's Board of Governors twice. He is a recipient of the National Science Foundation CAREER Award and the Canadian Natural Sciences and Engineering Research Council 1967 Graduate Fellowship. David has been honored with the Outstanding Teaching Award from the department of electrical engineering and computer sciences at the University of California, Berkeley, and he is a recipient of the American Society for Engineering Education's Frederick Emmons Terman Award, the National Academy of Engineering's Gilbreth Lectureship, and the IEEE Information Theory Society Claude E. Shannon Award.

David received a bachelor's degree in systems design engineering from the University of Waterloo in 1989, and MS and PhD degrees in electrical engineering from the Massachusetts Institute of Technology in 1992 and 1994, respectively.

David's contributions to the field of information theory and its applications make him a deserving candidate for the Thomas Kailath and Guanghan Xu Professorship in the School of Engineering.

 

Please join us in congratulating David on this achievement.

 

Related News:

2017 Claude E. Shannon Award, July 2016

David's EE Spotlight 

 

June 2017

If electric cars could recharge while driving down a highway, it would virtually eliminate concerns about their range and lower their cost, perhaps making electricity the standard fuel for vehicles.

Now Stanford University scientists have overcome a major hurdle to such a future by wirelessly transmitting electricity to a nearby moving object. Their results are published in the June 15 edition of Nature.

"In addition to advancing the wireless charging of vehicles and personal devices like cellphones, our new technology may untether robotics in manufacturing, which also are on the move," said Shanhui Fan, a professor of electrical engineering and senior author of the study. "We still need to significantly increase the amount of electricity being transferred to charge electric cars, but we may not need to push the distance too much more."

The group built on existing technology developed in 2007 at MIT for transmitting electricity wirelessly over a distance of a few feet to a stationary object. In the new work, the team transmitted electricity wirelessly to a moving LED lightbulb. That demonstration only involved a 1-milliwatt charge, whereas electric cars often require tens of kilowatts to operate. The team is now working on greatly increasing the amount of electricity that can be transferred, and tweaking the system to extend the transfer distance and improve efficiency.

"We can rethink how to deliver electricity not only to our cars, but to smaller devices on or in our bodies," Fan said. "For anything that could benefit from dynamic, wireless charging, this is potentially very important."

The study was also co-authored by former Stanford research associate Xiaofang Yu. Part of the work was supported by the TomKat Center for Sustainable Energy at Stanford.

 

Excerpted from Stanford News, "Wireless charging of moving electric vehicles overcomes major hurdle in new Stanford research," June 14, 2017.

June 2017

By Julie Chang, PhD candidate

The seventh annual IEEE International Conference on Computational Photography (ICCP) was hosted at Stanford University on May 12-14, 2017. Over 200 students, post-docs, professors, and entrepreneurs from around the world came together to discuss their research in this area. Professor Gordon Wetzstein from Stanford served as program chair alongside Laura Waller from UC Berkeley and Clem Karl from Boston University.

Wetzstein leads the Computational Imaging group at Stanford, which works on advancing the capabilities of camera and display technology through interdisciplinary research in applied math, optics, human perception, computing, and electronics. Active areas of research include virtual reality displays, advanced imaging systems, and optimization-based image processing. Wetzstein also teaches the popular Virtual Reality course (EE 267) as well as Computational Imaging and Displays (EE 367) and Digital Image Processing (EE 368). Several members of Wetzstein's lab presented their work at the conference. Isaac Kauvar (co-advised by Karl Deisseroth) and Julie Chang's paper on "Aperture interference and the volumetric resolution of light field fluorescence microscopy" was accepted for a talk. Posters and demos from Wetzstein's group included Nitish Padmanaban's provocatively titled project on "Making Virtual Reality Better Than Reality," Robert Konrad's spinning VR camera nicknamed "Vortex", and Felix Heide's domain-specific language "ProxImaL" for efficient image optimization.

ICCP 2017 was comprised of nine presentation sessions each with several accepted and invited talks organized around topics such as time-of-flight and computational illumination, image processing and optimization, computational microscopy, and turbulence and coherence. There was a mix of hardware and software projects for a wide variety of applications, ranging from gigapixel videos to seeing in the dark to photographic stenography. One keynote speaker was scheduled for each day. In Friday's keynote, Professor Karl Deisseroth (Stanford) discussed the importance of optical tools, namely optogenetics and advanced fluorescence microscopy, to help elucidate the inner working of the brain. The second keynote was given by Paul Debevec (USC/Google), who showed some of his team's work in computational relighting, both in Hollywood to make movies such as 'Gravity' possible, and in the White House to construct Barack Obama's presidential bust. The final keynote speaker was Professor Sabine Susstrunk (EPFL), who spoke on the non-depth-measurement uses of near-infrared imaging in computational photography.

The conference this year also included an industry panel on computational photography start-ups comprised of seasoned experts Rajiv Laroia of Light, Ren Ng of Lytro, Jingyi Yu, and Kartik Venkataraman of Pelican Imaging. Kari Pulli of Meta chaired a lively discussion covering the risks and thrills of startups, comparison with working at large companies, and the future of the computational photography industry.

The best paper award was received by Christian Reinbacher, Gottfried Munda, and Thomas Pock for their work on real-time panoramic tracking for event cameras. By popular vote, the best poster award was presented to Katie Bouman et al., for their work on "Turning Corners into Cameras," a method of seeing around corners by looking at the shadows produced at a wall corner, and the best demo award to Grace Kuo et al, for "DiffuserCam," which allows for imaging with a diffuser in place of a lens.

 

May 2017

Professor Stephen Boyd was awarded an honorary doctorate from the Institute of Statistics, Biostatistics and Actuarial Sciences of the Catholic University of Louvain for his achievements in the field of data sciences.

The awards ceremony was held earlier in May at the Universite Catholique de Louvain. Stephen participated in a roundtable discussion and presented on Convex Optimization.

 

Please join us in congratulating Stephen for this well deserved recognition of his profound contributions.

May 2017

A research team led by EE professor Jelena Vuckovic, has spent the past several years working toward the development of nanoscale lasers and quantum technologies that might someday enable conventional computers to communicate faster and more securely using light instead of electricity. Vuckovic and her team, including Kevin Fischer, a doctoral candidate and lead author of a paper describing the project, believe that a modified nanoscale laser can be used to efficiently generate quantum light for fully protected quantum communication. "Quantum networks have the potential for secure end-to-end communication wherein the information channel is secured by the laws of quantum physics," states PhD candidate Kevin Fischer.

Signal processing is helping the IoT and other network technologies to operate faster, more efficiently, and very reliably. Advanced research also promises to open new opportunities in key areas, such as highly secure communication and various types of wireless networks.

The biggest challenge the researchers have faced so far is dealing with the fact that quantum light is far weaker than the rest of the light emitted by a modified laser, making it difficult to detect. Addressing this obstacle, the team developed a method to filter out the unwanted light, enabling the quantum signal to be read much better. "Some of the light coming back from the modified laser is like noise, preventing us from seeing the quantum light," Fischer says. "We canceled it out to reveal and emphasize the quantum signal hidden beneath."

Despite being a promising demonstration of revealing the quantum light, the technique is not yet ready for large-scale deployment. The Vuckovic group is working on scaling the technique for reliable application in a quantum network.

 

Excerpted from "A Networking Revolution Powered by Signal Processing," IEEE Signal Processing Magazine, January 2017.
Read full article (opens PDF)

May 2017

"Quantum computing is ideal for studying biological systems, doing cryptography or data mining – in fact, solving any problem with many variables," states Professor Jelena Vuckovic"When people talk about finding a needle in a haystack, that's where quantum computing comes in."

 In her own studies of nearly 20 years,  Vuckovic has focused on one aspect of the challenge: creating new types of quantum computer chips that would become the building blocks of future systems.

"To fully realize the promise of quantum computing we will have to develop technologies that can operate in normal environments," she said. "The materials we are exploring bring us closer toward finding tomorrow's quantum processor."

The challenge for Vuckovic's team is developing materials that can trap a single, isolated electron. Working with collaborators worldwide, they have recently tested three different approaches to the problem, one of which can operate at room temperature – a critical step if quantum computing is going to become a practical tool.

In all three cases the group started with semiconductor crystals, material with a regular atomic lattice like the girders of a skyscraper. By slightly altering this lattice, they sought to create a structure in which the atomic forces exerted by the material could confine a spinning electron.

"We are trying to develop the basic working unit of a quantum chip, the equivalent of the transistor on a silicon chip," states Vuckovic. "We don't know yet which approach is best, so we continue to experiment."

 

 

 

Excerpted from the Stanford News, "Stanford team brings quantum computing closer to reality with new materials".

Photo credit: Amanda Law

May 2017

Electrical Engineering staff recognized for their outstanding effort include Fely Barrera, Daisy Chavez, John DeSilva and Helen Niu. Each were nominated by peers, faculty and/or students for professionalism that went above and beyond their everyday roles. Gift card recipients continue to make profound and positive impact in EE's everyday work and academic environment.

 

Please join us in congratulating Fely, Daisy, John and Helen. Excerpts from their nominations follow.

 

Fely Barrera, Administrative Associate

  • "Fely's willingness to help is greatly appreciated."
  • "She is a great resource for all of my questions."

Daisy Chavez, Graduate Admissions Specialist & Student Life Coordinator

  • "Daisy's support of student organizations, like WEE and OSA, is great! She clarifies everything and is willing to help us."
  • "She ensures our admissions process goes smoothly, all the while being a pleasure to work."

John DeSilva, Systems & Network Manager

  • "John is the definition of reliability!"
  • "He is always available, with endless patience for every question and need."

Helen Niu, Administrative Associate

  • "Helen is a pleasure to work with; she's resourceful and energetic."
  • "She is efficient, patient, and provides significant value to our research."

The Staff Gift Card Bonus Program is sponsored by the School of Engineering. Each year, the EE department receives several gift cards to distribute to staff members who are recognized for going above and beyond their role. Staff are chosen from nominations received from faculty, students, and staff. Past nominations are eligible for future months.

Nominate a deserving staff person or group today! We encourage you to nominate individuals or groups that have made a profound improvement in your daily work life. Each recipient receives a $50 Visa card. Nominations can be made at any time.

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