News

Eli Yablonovitch wins IEEE Edison Medal

Prof. Eli Yablonovitch has been awarded the 2018 Institute of Electrical and Electronics Engineers (IEEE) Edison Medal.  Named for Thomas Edison and presented since 1909, the IEEE Edison Medal is awarded for a career of meritorious achievement in electrical science, electrical engineering, or the electrical arts.  Yablonovitch, who co-founded the field of of photonic crystals, was cited for "For leadership, innovations, and entrepreneurial achievements in photonics, semi-conductor lasers, antennas, and solar cells.”

Profs. Sanjit Seshia and Pieter Abbeel

Pieter Abbeel and Sanjit Seshia elected 2018 IEEE fellows

Profs. Pieter Abbeel and Sanjit Seshia have been elected fellows of the Institute of Electrical and Electronics Engineers (IEEE) class of 2018.  The objectives of the IEEE, the world's largest association of technical professionals, are the educational and technical advancement of electrical and electronic engineering, telecommunications, computer engineering and allied disciplines.  The Fellow grade is the highest level of membership and is conferred by the IEEE Board of Directors in recognition of a high level of demonstrated extraordinary accomplishment.  Abbeel was selected "for contributions to apprenticeship and reinforcement learning for robotics and autonomous systems" and Seshia was selected for "for contributions to formal methods for inductive synthesis and algorithmic verification."

Institute for Advanced Study appoints Mark Heising to board of trustees

EE alumnus Mark Heising (M.S. '83) has been appointed to the board of trustees for The Institute for Advanced Study (IAS).  The IAS is one of the world’s leading centers for curiosity-driven basic research and serves as a model for protecting and promoting independent inquiry, prompting the establishment of similar institutes around the world, and underscoring the importance of academic freedom worldwide. Heising is the founder and managing director of Medley Partners, an investment firm based in San Francisco.  He previously worked as a chip design engineer and founded VLSI Cores--which designed and licensed cryptographic integrated circuits. He holds six U.S. patents in cryptography, compression, and data communications.

Woody Hoburg is 2017 R&D 100 Innovator of the Year

EECS alumnus Warren “Woody” Hoburg (MS'11, Ph.D.'13) was named R&D Magazine’s 2017 Innovator of the Year at the 55th annual R&D 100 Awards last Friday.  Hoburg recently left  his position as an assistant professor of Aeronautics and Astronautics at MIT when he was selected by NASA to join the 2017 Astronaut Candidate Class.  At MIT, Hoburg led a team that created an inexpensive, unpiloted aerial vehicle (UAV) that can keep itself aloft for more than five days — longer than any gasoline-powered autonomous aircraft has remained in flight. The technology, which has a variety of applications including providing wide-ranging communications support in the event of a natural disaster, is currently under development for the U.S. Air Force.

Bernd Sturmfels wins 2018 George David Birkhoff Prize in Applied Mathematics

CS Prof. Bernd Sturmfels has won the 2018 George David Birkhoff Prize in Applied Mathematics for "his instrumental role in creating the field of applied algebraic geometry." This prize is jointly awarded by the American Math Society (AMS) and the Society for Industrial and Applied Math (SIAM) every 3 years for "an outstanding contribution to applied mathematics in the highest and broadest sense." Previous winners include Emmanuel Candes, Bjorn Engquist, and many other luminaries.

Jennifer Listgarten joins EECS Department

Dr. Jennifer Listgarten will join the EECS faculty effective Jan 1, 2018.  Listgarten received her B.S. in CS and Physics at Queen's University in Canada, and her M.S. (CS/computational vision) and Ph.D. (CS/bioinformatics/machine learning) from the University of Toronto.  She has spent the past 10 years as a researcher at Microsoft; her area of expertise is machine learning and applied statistics for computational biology.   She is interested in both methods development as well as application of methods to enable new insight into basic biology and medicine.  She will be co-teaching CS189 Introduction to Machine Learning with Prof. Anant Sahai starting in January.

C. L. Hoang publishes "Rain Falling on Tamarind Trees"

A  new book, Rain Falling on Tamarind Trees, by EE alumnus C. L. Hoang (M.S. '82), is set to be released by Willow Stream Publishing tomorrow.  Hoang was born and raised in Vietnam during the war and came to the US in the 1970s.  He wrote this travelogue about his experiences returning to his ancestral homeland for the first time, in 2016, after a decades-long absence.   He still makes his living as an engineer--he holds 11 patents--and says that his engineering training helped him hone his organizational skills and develop an analytical eye for details as well as a love for research.  His first book, Once upon a Mulberry Field, is a historical novel set in Vietnam during the height of the war.

professor ruzena bajcsy

Philly honors Ruzena Bajcsy

The life and contributions of CS Prof. Ruzena Bajcsy are profiled in a Philadelphia Inquirer article titled "Philly honors experts in robotics, genetics, evolution."  Bajcsy, who helped launch the field of computer vision, is being presented with a John Scott Award in science and medicine at the American Philosophical Society this evening.  Her early research paved the way for medical imaging such as MRIs, and she is noted for her cross-disciplinary approach, applying theories from mathematics and biology to her work.  She has devoted her life to research in the fields of robotics, artificial intelligence and machine perception, and took the helm of the Center for Information Technology Research in the Interest of Society (CITRIS) from 2001 to 2005.  Recipients of the Scott Awards are chosen each year based on recommendations from a panel of scientists. The award comes with a $10K prize.

Sanjay Mehrotra named Vice Chair of SIA

Alumnus Sanjay Mehrotra (EECS B.S. '78/M.S. '80) has been named the 2018 Vice Chair of the Semiconductor Industry Association (SIA).  The SIA is a trade association and lobbying group positioned as "the voice of the U.S. semiconductor industry."  Mehrotra, who is currently CEO of Micron, led the growth of SanDisk Corporation from start-up in 1988 to Fortune 500 company in 2016.  He holds 70 patents and has published articles on nonvolatile memory design and flash memory systems.

Stampede2 (Sean Cunningham / TACC)

EECS-affiliated team break record for fastest deep learning training

Grad student Yang You, Prof. James Demmel and Prof. Kurt Keutzer, along with Prof. Cho-Jui Hsieh of UC Davis and Dr. Zhao Zhang of the Texas Advanced Computing Center (TACC), have created, in collaboration with researchers at NVIDIA, a new algorithm which enables them to harness the power of supercomputers to train a deep neural network (DNN) for image recognition at record speed. Deep learning researchers currently use trial-and-error to design new models, requiring them to run training processes tens or even hundreds of times for each model.  The team's effort efficiently used 1024 Skylake processors on the Stampede2 supercomputer at TACC to complete a 100-epoch ImageNet training with AlexNet in 11 minutes - the fastest time recorded to date.  Also, using 1600 Skylake processors, they bested Facebook's prior results by finishing a 90-epoch ImageNet training with ResNet-50 in 32 minutes and, for batch sizes above 20,000, their accuracy was much higher than Facebook's.   The group's breakthrough involved the development of the Layer-Wise Adaptive Rate Scaling (LARS) algorithm that is capable of distributing data efficiently to many processors to compute simultaneously using a larger-than-ever batch size (up to 32,000 items). The LARS algorithm was jointly developed with Nvidia. The findings show an alternative to the trend of using specialized hardware - either GPUs, Tensor Flow chips, FPGAs or other emerging architectures—for deep learning. The team wrote the code based on Caffe and utilized Intel-Caffe, which supports multi-node training. The results are published in Arxiv.