Faculty

September 2017


In the Future of Everything radio show, Kwabena Boahen discusses the evolution of computers and how the next big step forward will be to design chips that behave more like the human brain.

Boahen is a professor of bioengineering and electrical engineering, exploring in his lab how these chips can interface with drones or with the human brain. "It's really early days," he says.


In partnership with SiriusXM, Stanford University launched Stanford Radio, a new university-based pair of radio programs. The programs are produced in collaboration with the School of Engineering and the Graduate School of Education.

"The Future of Everything" is from the School of Engineering and "School's In" is from the Graduate School of Education.

 

Kai Zang (PhD '17)
October 2017

Kai Zang's (PhD '17) paper published in Nature Communications describes how nanotextured silicon can absorb more photons, furthering the effectiveness of solar cells. This research also resulted in a second discovery – improving the collision-avoidance technology in vehicles.

Professor Jim Harris said he always thought Zang's texturing technique was a good way to improve solar cells. "But the huge ramp up in autonomous vehicles and LIDAR suddenly made this 100 times more important," he says.

The researchers figured out how to create a very thin layer of silicon that could absorb as many photons as a much thicker layer of the costly material. Specifically, rather than laying the silicon flat, they nanotextured the surface of the silicon in a way that created more opportunities for light particles to be absorbed. Their technique increased photon absorption rates for the nanotextured solar cells compared to traditional thin silicon cells, making more cost-effective use of the material.

After the researchers shared these efficiency figures, engineers working on autonomous vehicles began asking whether this texturing technique could help them get more accurate results from a collision-avoidance technology called LIDAR, which is conceptually like sonar except that it uses light rather than sound waves to detect objects in the car's travel path.

In their Nature Communications paper, the team reports that their textured silicon can capture as many as three to six times more of the returning photons than today's LIDAR receivers. They believe this will enable self-driving car engineers to design high-performance, next-generation LIDAR systems that would continuously send out a single laser pulse in all directions. The reflected photons would be captured by an array of textured silicon detectors, creating moment-to-moment maps of pedestrian-filled city crosswalks.

Harris said the texturing technology could also help to solve two other LIDAR snags unique to self-driving cars – potential distortions caused by heat and the machine equivalent of peripheral vision. The Harris Group research website. 

 

 

Excerpted from "A new way to improve solar cells can also benefit self-driving cars," Stanford Engineering, October 2, 2017.

John Hennessy and Philip Knight. Image credit: L.A. Cicero
September 2017

The Knight-Hennessy Scholars program will be lead by EE professor and Stanford's former president John Hennessy. The program is funded by philanthropist Philip Knight (MBA '62).

The program aims to prepare a new generation of leaders with the deep academic foundation and broad skill set needed to develop creative solutions for the world's most complex challenges.

Fifty scholars will join the first cohort that enrolls in fall 2018, with up to 100 scholars admitted annually in subsequent years. Scholars will comprise an interdisciplinary graduate community representing a wide range of backgrounds and nationalities.

Building on his or her core Stanford graduate degree program, each scholar will participate in opportunities for leadership training, mentorship and experiential learning across multiple disciplines. Knight-Hennessy Scholars will receive financial support for the full cost of attendance to pursue a graduate education at Stanford.

"We recognize that an application cannot fully reflect who Knight-Hennessy Scholars are and how they live," said Derrick Bolton, dean of Knight-Hennessy Scholars admission. "We believe it's essential that we learn not only about what they have done, but also who they are: their influences, ideals, hopes and dreams."

The program's faculty advisory board and global advisory board, respectively comprising faculty from all seven schools and leaders from business, government, health care, law, technology and other fields, shaped the criteria to guide the selection of scholars. The Knight-Hennessy Scholars admission committee will consider three primary criteria when evaluating applications: independence of thought, purposeful leadership and a civic mindset.

Up to 100 application finalists will be invited to attend Immersion Weekend, which will take place at Stanford in January 2018.

"Immersion Weekend will be an experience that is fun, informal and informative for applicants," Bolton said. "Our aim is that the candidates will learn more about the graduate programs, the Knight-Hennessy Scholars program and themselves. It also gives a chance for the departments and us to get to know the applicants better."

In addition to submitting the Knight-Hennessy Scholars application, applicants must also apply to the Stanford graduate program of their choice.

 

Additional information available Knight-Hennessy.stanford.edu

 

Excerpted from "Knight-Hennessy Scholars launches inaugural application," May 2017.

Professor Lambertus 'Bert' Hesselink
August 2017

The paper, "Visualization of Second Order Tensor Fields and Matrix Data," was coauthored by professor Bert Hesselink and Thierry Delmarcelle in 1992. This paper describes some of their work on mathematical topology related to data analysis and lossless compression and visualization of tensor and vector data sets. The committee selected this paper for its importance and long term impact.

The IEEE VIS Test of Time Award is an accolade given to recognize articles published at previous conferences whose contents are still vibrant and useful today and have had a major impact and influence within and beyond the visualization community.

Papers are selected for each of the three conferences (VAST, InfoVis and SciVis) by Test of Time Awards panels appointed by the conference Steering Committees.

The decisions are based on objective measures such as the numbers of citations, and more subjective ones such as the quality and longevity and influence of ideas, outreach, uptake and effect not only in the research community, but also within application domains and visualization practice.

A full rationale will be provided for each paper at the conference opening, where we hope to encourage researchers to aim to produce work that is forward looking and has transformational potential. We're trying to build on our heritage to establish an ambitious future by making it clear at the outset of the conference opening that we want participants to aspire to be writing papers today that will be relevant in decades to come.

Professor Hesselink's research encompasses nano-photonics, ultra high density optical data storage, nonlinear optics, optical super-resolution, materials science, three-dimensional image processing and graphics, and Internet technologies.

 

Congratulations to Bert on this well-deserved recognition.

 

IEEE 2017 Test of Time Awards

Photo credit, The Marconi Society
August 2017

Engineering Professor emeritus Thomas Kailath will be given the Marconi Society's Lifetime Achievement Award in recognition of his many transformative contributions to information and system science, as well as his sustained mentoring and development of new generations of scientists.

Kailath is the sixth scientist to be honored with a Marconi Society Lifetime Achievement Award. The society is dedicated to furthering scientific achievements in communications and the internet.

"The award is being conferred on Kailath for mentoring a generation of research scholars and writing a classic textbook in linear systems that changed the way the subject is taught and his special purpose architecture to implement the signal processing algorithms on VLSI (Very Large-scale System Integration) chips," the society said.

Kailath's research and teaching at Stanford have ranged over several fields of engineering and mathematics, with a different focus roughly every decade.

 

Please join us in congratulating Tom for this very special recognition. Tom will receive his award at the annual Marconi Society Awards dinner in October.

 

Excerpted from Stanford News, "Stanford electrical engineering Professor Thomas Kailath honored for lifetime achievement by Marconi Society," August 16, 2017.

The Marconi Society press release, "Legendary Stanford Professor Thomas Kailath Will Receive The Marconi Society Lifetime Achievement Award," August 14, 2017. 

 

 

Related News

Professor Emeritus Thomas Kailath Awarded Honorary Degree, April 2017

Tom Kailath selected as Eminent Member, IEEE-HKN, February 2017

Professor Kailath Receives National Medal of Science from President Obama, October 2014

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.

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.

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