Mattel has launched a line of biologically inspired foldable robot bugs designed in collaboration with Dash Robots, a spin-off of the Biomimetic Millisystems Lab (BML).  The researchers at BML, under the direction of Prof. Ron Fearing, draw inspiration from nature to build more efficient robotics.  The new toys, called  Kamigami, let kids build their own robotic bugs, like mantises, ladybugs and scorpions.  Each $50 kit contains parts of a six-legged robot (with an accelerometer, gyroscope, and IR transmitter/receiver) and foldable plastic origami sheets to transform each robot into a different creature.

EE Prof. Alberto Sangiovanni-Vincentelli has been appointed Non-Executive Chairman of UltraSoC, a pioneering semiconductor IP technology start-up based in Cambridge, UK.  The appointment comes as the company drives accelerating adoption of its IP for debug during chip design, and of its embedded intelligent analytics capabilities for monitoring wider system performance on all processor platforms: in particular the open-source RISC-V architecture.  Sangiovanni-Vincentelli helped to found both Cadence Design Systems and Synopsys – the two industry leaders in Electronic Design Automation (EDA).   CEO Rupert Baines says “We are excited to welcome Alberto into the Chairman role and are convinced that his background as a serial entrepreneur and distinguished academic makes him the ideal choice for guiding UltraSoC’s future growth and direction.” UltraSoC’s technology is now enhancing safety, security and power for system design, in applications including automotive, enterprise IT, and the Internet of Things (IoT).

Berkeley DeepDrive (BDD) and Nexar announced the release of 36,000 high frame-rate videos of driving, in addition to 5,000 pixel-level semantics-segmented labeled images, and invited public and private institution researchers to join the effort to develop accurate automotive perception and motion prediction models.  The BDD Industry Consortium, led by EE Prof. Trevor Darrell , investigates state-of-the-art technologies in computer vision and machine learning for automotive applications. Nexar, as a member of the consortium, contributes video and images captured by its road safety AI camera application deployed in over 100 countries worldwide.  The Nexar driving data will be used for academic research (for activities like training and validating models for real world applications) as well as open crowdsourced research challenges based on parts of the driving data.

Teaching Prof. Dan Garcia is featured in an EdSurge article titled "Engineers, Recruiters and Professors Weigh In: Future Programmers Need Writing Skills, Too," in which he discusses how career goals should shape a student's skill set.  Although not all successful coders need to be proficient writers, flexibility is important.  “There are careers where someone doesn't need [to write]… but we want students to be able to go to any position. Maybe they want to just be a coder [at first], but later they decide to be an academic or on the documentation side or in management,” says Garcia. “My point is you never know when you need to write.”

In a somewhat related Daily Cal article, undergrad Sanil Rajput ponders the correlation between copy editing and computer science, putting forth a theory that "Copy editors make excellent coders."

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.

Turing Award-winning computer scientist Shafi Goldwasser will become the new Director of the Simons Institute for the Theory of Computing at the University of California, Berkeley, on January 1, 2018. The Simons Institute is the world's leading venue for collaborative research in theoretical computer science. Established on July 1, 2012 with a grant of $60 million from the Simons Foundation, the Institute is housed in Calvin Lab, a dedicated building on the UC Berkeley campus. The Simons Institute brings together the world's leading researchers in theoretical computer science and related fields, as well as the next generation of outstanding young scholars, to explore deep unsolved problems about the nature and limits of computation.

Professor Shafi Goldwasser is one of the giants of theoretical computer science, and one of its most original thinkers. She has made foundational contributions to the field of cryptography – for which she received the 2012 Turing Award – including inventing semantically secure probabilistic encryption, pseudorandom functions, and zero-knowledge proofs. She has also made outstanding contributions to computational complexity theory, including the development of interactive proof systems, and the discovery of their connection to the complexity of approximation, for which she received the Gödel Prize in 1993 and 2001.

“Algorithms govern our computing-based world in the same way that the laws of nature govern the physical one,” says Goldwasser. “Their mathematical underpinnings are thus as important to modern society as the periodic table, relativity, or the genome. The Simons Institute at Berkeley, under my leadership, will continue its dedication to the discovery of the fundamentals of computation and to findings that enable technological progress and positive social change.”

 In addition to her appointment as Director of the Simons Institute, Professor Goldwasser will be a faculty member in Department of Electrical Engineering and Computer Sciences at Berkeley, and in both places she will continue her track record of outstanding mentorship; her former students rank among the leaders of the field of theoretical computer science.

 Goldwasser has been a faculty member at the Massachusetts Institute of Technology since 1983, and in 1997 became the first holder of the RSA Professorship (named after the inventors of the first public-key cryptosystem, Rivest, Shamir and Adleman). Concurrently with her professorship at MIT, she has been a professor at the Weizmann Institute of Science since 1993. She was elected to the American Academy of Arts and Sciences in 2001, the National Academy of Sciences in 2004, and the National Academy of Engineering in 2005. Her awards include the ACM Grace Murray Hopper Award (1996), the RSA Award In Mathematics (1998), the ACM Athena Lecturer Award (2009), the Benjamin Franklin Award in Computer and Cognitive Science (2010), and the IEEE Emanuel Piore Award (2011).

 Goldwasser’s appointment is the culmination of a worldwide search for the next Director of the Simons Institute, to replace Founding Director Richard Karp, who steps down at the end of this year after a five-year term. Goldwasser will take the helm as Director of the Institute in January, and will relocate to Berkeley from Cambridge, Massachusetts in the summer of 2018.

 “We are delighted that someone of Shafi's formidable intellect and capacity for innovation will be joining the UC Berkeley community. We are excited for her contributions to campus intellectual life,” says UC Berkeley Chancellor Carol Christ. “In the five years since its founding, the Simons Institute for the Theory of Computing has become a flagship institution on campus, and a worldwide center of excellence in theoretical computer science. We’re certain that under Shafi's leadership, the Institute will be on a trajectory to make an even deeper impact on the theory of computing and related areas in computer science, engineering, and the physical and social sciences.”

 Also new to the Institute’s leadership team is Berkeley computer science and statistics professor Peter Bartlett, who took over as Associate Director on July 1, 2017. The position was formerly held by Alistair Sinclair, the Institute’s Founding Associate Director, who stepped down at the end of his second term this summer. Bartlett is a world leader in statistical learning theory, a field that provides the theoretical underpinnings of machine learning. While his work focuses on the underlying theory, it has in many cases influenced practical applications as well.

Bartlett has contributed to many areas of statistical learning theory, including large margin classifiers, boosting methods, kernel methods, reinforcement learning, Rademacher averages, online learning methods, and neural networks. He has published over 150 papers and is co-author of the book, Learning in Neural Networks. He has held a visiting Miller Professorship at Berkeley, an honorary professorship at the University of Queensland, and a visiting professorship at the University of Paris. Bartlett was awarded the Malcolm McIntosh Prize for Physical Scientist of the Year in Australia in 2001, and was chosen as an Institute of Mathematical Statistics Medallion Lecturer in 2008, and an IMS Fellow and Australian Laureate Fellow in 2011. He was elected to the Australian Academy of Science in 2015.

 Continuing on as a permanent member of the Institute’s scientific leadership is Senior Scientist Luca Trevisan, a distinguished complexity theorist and Professor of Computer Science at UC Berkeley, whom Berkeley recruited from Stanford to play a leading role at the Simons Institute.

 This summer, the Simons Institute for the Theory of Computing marked the five-year anniversary of its founding in 2012. During this initial period, the Institute has established itself as the world’s preeminent center for collaborative research in theoretical computer science.

 Over a thousand visiting scientists have participated in the Institute’s semester-long research programs exploring foundational questions in data science, machine learning, evolutionary biology, quantum computing, genomics, computational economics, and many other topics. An announcement from the Association for Computing Machinery (ACM) Special Interest Group on Algorithms and Computation (SIGACT) this summer praised “the spectacular success of the Simons Institute for the Theory of Computing in taking collaboration in our field to an entirely new level,” describing it as “a game-changer for Theory.”

The Department of EECS is pleased to announce the appointment of Nir Shavit as Visiting Professor, effective July 1, 2018. Shavit is a leading researcher in the field of distributed and parallel computation. The central issue in this area is managing a shared memory across a number of processors while maintaining consistency and avoiding conflicts. Shavit has made foundational contributions to this field, ranging from abstract theorems introducing a topological framework for analyzing these issues to providing a practical, and widely used, realization of a transactional memory technique for multiprocessor synchronization. A recent focus of Shavit’s work has been the application of parallel computation to “connectomics”: the creation of detailed maps of the connections in the brain.

Shavit received the M.Sc. in 1985 from Technion and the Ph.D. in Computer Science in 1990 from the Hebrew University of Jerusalem. He is on the faculty of  Tel Aviv University, where he began as a Lecturer in 1992 and rose through the ranks to full professor in 2007. Since 2011, he has also been a full professor at MIT .

 Two of Shavit’s co-authored papers have received distinguished prizes from the European Association for Theoretical Computer Science and the Association for Computing Machinery: The Gödel Prize in 2004 for the paper “The Topological Structure  of Asynchronous Computation”  and the Dijkstra Prize in 2012 for the paper “Software Transactional Memory.” The massive textbook, The Art of Multiprocessor Programming,” by Maurice Herlihy and Shavit (2008) is the most authoritative treatment of this subject.

 In view of his outstanding conceptual and practical achievements and his exceptional skills as an expositor Shavit will be a major contributor to Berkeley’s efforts in parallel and distributed computing.

A team of U.C. Berkeley researchers including Associate Prof. Chunlei Liu, Prof. Ana Arias, and Associate Prof. Michael Lustig, has been awarded a $13.43 million grant by the National Institutes of Health (NIH) as part of the Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative.  The team will use the money to build the NexGen 7T, an innovative functional magnetic resonance imaging (fMRI) scanner designed to provide the highest resolution images of the brain ever obtained.  Liu, an MR imaging specialist,  is the project co-leader along with physicist David Feinberg of the Helen Wills Neuroscience Institute.  The new scanner, which will boost resolution by a factor of 20, will give neuroscientists the ability to focus on cortical layers where most neuronal circuitry resides as well as to better identify large-scale circuitry connecting different regions of the brain.   Arias is an expert on flexible electronics and Lustig has developed new ways to speed up MRI scanning. The researchers will collaborate with Siemens to insure that the design can be quickly ramped up to produce next-generation scanners for researchers around the world.