Three papers with Berkeley authors received the Helmholtz Prize at the International Conference on Computer Vision (ICCV) 2017 in Venice, Italy.  This award honors  papers that have stood the test of time (more than ten years after first publication) and is bestowed by the IEEE technical committee on Pattern Analysis and Machine Intelligence (PAMI).    Seven papers won this year, among them: "Recognizing action at a distance," by A Efros, A Berg, G Mori and J Malik, ICCV 2003; "Discovering objects and their location in images," by J Sivic, B Russell, A Efros, A Zisserman and W Freeman, ICCV 2005; and "The pyramid match kernel: Discriminative classification with sets of image features," by K Grauman and T Darrell, ICCV 2005."

EE Associate Prof. Chunlei Liu has co-authored a study which has identified a specific molecular pathway that links maternal fever early in pregnancy to some congenital heart and cranial facial birth defects.  The findings, which were published in the journal Science Signaling, suggest a portion of congenital birth defects could be prevented if fevers are treated through the judicious use of acetaminophen during the first trimester.  Among their discoveries, the scientists found that neural crest cells—which are critical building blocks for the heart, face and jaw—contain temperature-sensitive properties.  “With electrical magnetic waves coupled with engineered ion channel proteins, we are able to impact specific biological cells remotely without affecting other biochemical environments,” Liu said. “The technique can be applied to study many different cell types and their roles at various developmental stages.”  The research was conducted in collaboration with scientists at Duke Universiy.

Computer Science faculty in the Real-Time Intelligent Secure Execution Lab (RISELab) have outlined challenges in systems, security and architecture that may impede the progress of Artificial Intelligence, and propose new research directions to address them.  The paper, A Berkeley View of Systems Challenges for AI, was authored by Profs. Stoica, Song, Popa, Patterson, Katz, Joseph, Jordan, Hellerstein, Gonzalez, Goldberg, Ghodsi, Culler and Abbeel, as well as Michael  Mahoney in Statistics/ICSI. Some of the challenges outlined include AI systems that make timely and safe decisions in unpredictable environments, that are robust against sophisticated adversaries, and that can process ever increasing amounts of data across organizations and individuals without compromising confidentiality.

EE Prof. Edward A. Lee has published his first book for a general audience, Plato and the Nerd: The Creative Partnership of Humans and Technology  (MIT Press, 2017).  In it, Lee observes that engineering is a deeply intellectual and fundamentally inventive process and that the producers of digital technology have an unsurpassed medium for creativity.   Janos Sztipanovits writes in his review "Lee's book is a brilliant articulation of the unique and increasingly important role technology plays in the evolution of mankind. He offers a deeply optimistic perspective with clarity and intellectual rigor without ever losing accessibility."  Lee has previously coauthored several textbooks on topics including digital communication, signal processing, embedded systems, and software modeling.

CS graduate student Aviad Rubinstein (advisor: Christos Papadimitriou)  is featured in a Quanta Magazine article titled "In Game Theory, No Clear Path to Equilibrium," which describes the results of his paper on game theory proving that no method of adapting strategies in response to previous games will converge efficiently to even an approximate Nash equilibrium for every possible game. The paper, titled Communication complexity of approximate Nash equilibria, was co-authored by Yakov Babichenko and published last September.  Economists often use Nash equilibrium analyses to justify proposed economic reforms, but the new results suggest that economists can’t assume that game players will get to a Nash equilibrium, unless they can justify what is special about the particular game in question.

The paper titled "ESPIRiT—an eigenvalue approach to autocalibrating parallel MRI: Where SENSE meets GRAPPA" co-written by Associate Prof. Michael Lustig,  his graduate student Pat Virtue, and alumnus Mark J. Murphy (Ph.D. '11 advisor: Kurt Keutzer) has been named the most-cited Magnetic Resonance in Medicine article from 2014.    The article bridges the gap between the two main approaches for parallel imaging (SENSE and GRAPPA) allowing the reconstruction of images from undersampled multicoil data.  It presents a new autocalibration technique combining the extended reconstruction of SENSE with GRAPPA-like robustness to errors.

Authors of the paper are listed as Martin Uecker, Peng Lai, Mark J. Murphy, Patrick Virtue, Michael Elad, John M. Pauly, Shreyas S. Vasanawala, and Michael Lustig.

U.C. Berkeley has the top ten most AMiner Most Influential Scholar Award winners across all fields of computer science in 2016 and the top five most award winners in the fields of Computer Vision, Database, Machine Learning, Multimedia, Security, Computer Networking, and System.  The 28 CS faculty members included in the rankings were among the 100 most-cited authors in 12 of the 15 research areas evaluated. Two were among the 100 most-cited authors in 3 different areas each: Scott Shenker ranked #1 in Computer Networking, #51 in System, and #99 in Theory; and Trevor Darrell ranked #8 in Mulitmedia, #18 in Computer Vision, and #100 in Machine Learning.  Out of the 700,000 researchers indexed, only 16 appeared on three or more area top 100 lists.  See a more detailed breakdown of our influential faculty scholars.

Dr. Scott Beamer's dissertation titled "Undertanding and Improving Graph Algorithm Performance" has been selected to receive the 2016 Standard Performance Evaluation Corp (SPEC) Kaivalya Dixit Distinguished Dissertation Award.  The award recognizes outstanding doctoral dissertations in the field of computer benchmarking, performance evaluation, and experimental system analysis in general.  Papers are evaluated on scientific originality, scientific significance, practical relevance, impact, and quality of the presentation.

Among other comments, the members of the committee were impressed with Beamer's deep understanding of open-source graphs, with the quality of the implementations, with the creation of a graph benchmark suite that is already been used, that is relevant for High Performance Computing, and that is likely to have further impact in the future. The committee also remarked on the clarity and simplicity of the ideas presented in the document.

The award will be presented at the International Conference on Performance Engineering (ICPE) in April.

Prof. Sergey Levine, EECS alumni Oriol Vinyals and EECS postdoc Wei Gao (working with Ali Javey) have been named on MIT Technology Review’s 2016 TR35 (Innovators Under 35) who push the edge of science, creating new approaches to tackling technology challenges. In the “Pioneers” category Prof. Levine teaches robots to watch and learn from their own successes, supervising it’s own learning, and Oriol Vinyals is working to create computers that can teach themselves how to play and win complex games by enabling them to learn from experience. In the “Inventors” category, Wei Gao is building sweatbands that monitor your health on a molecular level.

The research of Prof. Ron Fearing and Mechanical Engineering graduate student Carlos Casarez on cooperative step climbing is featured on the NSF Engineering Discoveries website in an article titled “Roach-like robots run, climb and communicate with people”. Since the 1990’s, Prof. Fearing has been developing biomimetic robots capable or remarkable feats of speed and maneuverability.