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.

EECS alumnus and security expert Alex Stamos (B.S. '01) is profiled in an article in Recode about his role as Facebook's Chief Security Officer.  He is currently leading their internal investigation into Russian meddling in the 2016 presidential election and co-authored a paper explaining how Russia carried out its misinformation campaign. The article describes Stamos's experiences as CSO of Yahoo and his efforts to protect the internet's rank-and-file users. “We’ve been asking people to pay attention to us for over 20 years. And they are,” he said. “We have the world’s attention. What are we going to do with it?”

CS Prof. Pieter Abbeel, graduate student Chelsea Finn, and Brett the robot are featured in a Wired article titled "The Education of Brett the Robot" which delves into some of the nuts and bolts of machine learning.  Brett (short for Berkeley Robot for the Elimination of Tedious Tasks) is using a reinforcement learning algorithm to allow it to learn from its mistakes.  Abbeel will speak on "Deep Learning-to-Learn Robotic Control" at the EECS Colloquium on October 11th.

Chancellor's Professor of Electrical Engineering and Neuroscience Jose Carmena, and Prof. Michel Maharbiz, are the subjects of a California Magazine article titled "Dust in the Machine," about brain-machine interface (BMI) research.  In 2013, Carmena, Maharbiz, then-graduate student Dongjin Seo (Ph.D. '16), Prof. Jan Rabaey, and Prof. Elad Alon published a paper on a new kind of implantable bioelectronics--a neural interface called "neural dust"--that was the size of a 1-millimeter cube, wireless, battery-less, and small enough to be placed in the peripheral nervous system and muscles.  The article describes BMI systems and subsequent technological advances and challenges.  Carmena is also co-director of the Center for Neural Engineering and Prostheses at Berkeley and UCSF.

EECS alumnus Shahin Farshchi (B.S. '02) is the subject of one of a series of Iranian Americans’ Contributions Project (IACP) interviews that explore the personal and professional backgrounds of prominent Iranian-Americans who have made seminal contributions to their fields. Farshchi is currently a Partner at Lux Capital Management where he has sourced many of the firm's investments in energy and technology.  In "Shahin Farshchi: Making the ‘Impossible’ Possible Through Feats of Engineering,"  he describes his intercultural childhood in the Bay Area and Iran, and discusses his philosophy, career, and outlook on developing technologies.  Before Lux, Farshchi held engineering positions at Aurorasoft, Telegenisys, General Motors, and Intelligent Control Systems.  He has published research on wireless biosignal telemetry.

CS alumnus Garth Gibson  (M.S. '84/B.S. '91) has been named CEO of the Vector Institute for Artificial Intelligence in Toronto, Canada.  The newly-formed Vector has received $50-million funding from Ontario and $85-million-plus from more than 30 companies, including Shopify Inc., Magna International Inc., Canada's big banks and U.S. tech giants including Google Inc.  Gibson, who is a native of Canada, has held several senior positions at Pittsburgh's Carnegie Mellon University, where he is a computer-science professor and established the school's Parallel Data Lab and Petascale Data Storage Institute.

CS Prof. Emeritus Lotfi Zadeh has posthumously won a 2017 Golden Goose Award for "Fuzzy Logic, Clear Impact," sponsored by the American Association for the Advancement of Science (AAAS).  The award honors teams of scientists whose silly-sounding taxpayer-funded research has returned serious benefits to society.  "Zadeh proposed these revolutionary concepts in 1965 to deal with the mathematics and logic of imprecise information, receiving a skeptical response and howls of 'complete nonsense.' He even drew the attention of Senator William Proxmire and the infamous Golden Fleece Award. But since the concept's debut, the original research paper has become one of the most widely cited in history, used in more than 16,000 patents and applied to efficiency improvements for HVAC systems, healthcare devices and more."  The winners will be honored at a ceremony at the Library of Congress this evening."  Prof. Zadeh passed away earlier this month.

CS Assistant Prof. Anca Dragan is one of the subjects of a San Francisco Chronicle article titled "Humanizing cars, sensitizing humans,"  about how the rise of robot vehicles will require reprogramming our relationship with them.  Dragan was interviewed for the section on "emotional intelligence" and what a robot car sees.  She said driverless cars will need to predict what humans on the road will do — and figure out how to behave appropriately around them.  Dragan is testing a computer model of an autonomous vehicle which nudges toward the adjacent lane and detects whether the simulated human driver hits the brakes or the accelerator, fairly similar to how most people change lanes.  “Those reactions tell it about your driving style, so it can anticipate whether it should merge or let you go first,” she said. “We’re excited to see that the car can ‘reason’ properly about people.”