News

Sanjit Seshia wins Computer-Aided Verification Award

EECS Prof. Sanjit Seshia was a recipient of the CAV Award at the 2021 International Conference on Computer-Aided Verification (CAV) earlier this month.  This award is presented annually "for fundamental contributions to the field of Computer-Aided Verification," and comes with a cash prize of $10K that is shared equally among recipients.  This year's award specifically recognizes pioneering contributions to the foundations of the theory and practice of satisfiability modulo theories (SMT).”  Seshia's Ph.D. thesis work on the UCLID verifier and decision procedure helped lay the groundwork for this field.  SMT solvers are critical to verification of software and hardware model checking, symbolic execution, program verification, compiler verification, verifying cyber-physical systems, and program synthesis. Other applications include planning, biological modeling, database integrity, network security, scheduling, and automatic exploit generation.  CAV is the premier international conference on computer-aided verification and  provides a forum for a broad range of advanced research in areas ranging from model checking and automated theorem proving to testing, synthesis and related fields.

NSF awards $20M for researchers to launch National AI Institute for Advances in Optimization

A team of researchers from UC Berkeley, Georgia Tech, and USC, have been awarded $20M by the National Science Foundation (NSF) to launch an institute which will deploy AI to tackle massive optimization challenges.  The researchers hope the new National Artificial Intelligence (AI) Institute for Advances in Optimization will deliver a paradigm shift in automated decision-making by fusing AI and optimization to address grand challenges in highly constrained settings, such as logistics and supply chains, energy and sustainability, and circuit design and control.  EECS/IEOR Prof. Pieter Abbeel will lead the Reinforcement Learning Team, and EECS/IEOR Prof. Laurent El Ghaoui will be on both the End to End Optimization and the New Learning Methods Teams.  EECS Profs. Borivoje Nikolic and Vladimir Stojanovic will also be participating.  The group intends to integrate ethics and values into their complex systems design, from inception through operation, to ensure that all scientific advances will ultimately serve the interests of society.  The institute also plans to partner with historically Black colleges and universities (HBCUs) in Georgia, and Hispanic-serving community colleges in California, to build longitudinal education and workforce development programs.  Partners include Clark Atlanta University, Spelman College, and the University of Texas at Arlington.

New AI system allows legged robots to navigate unfamiliar terrain in real time

A new AI system, Rapid Motor Adaptation (RMA), enhances the ability of legged robots, without prior experience or calibration, to adapt to, and traverse, unfamiliar terrain in real time.  A test robot figured out how to walk on sand, mud, and tall grass, as well as piles of dirt, pebbles, and cement, in fractions of a second.  The project is part of an industry-academic collaboration with the Facebook AI Research (FAIR) group and the Berkeley AI Research (BAIR) lab that includes CS Prof. Jitendra Malik as Principal Investigator, his grad student Ashish Kumar as lead author, and alumnus Deepak Pathak (Ph.D. 2019, advisors: Trevor Darrell and Alexei Efros), now an assistant professor at Carnegie Mellon, among others.  RMA combines a base policy algorithm that uses reinforcement learning to teach the robot how to control its body, with an adaptation module that teaches the robot how to react based on how its body moves when it interacts with a new environment.  “Computer simulations are unlikely to capture everything,” said Kumar. “Our RMA-enabled robot shows strong adaptation performance to previously unseen environments and learns this adaptation entirely by interacting with its surroundings and learning from experience. That is new.”  RMA's base policy and adaptation module run asynchronously and at different frequencies so that it can operate reliably on a small onboard computer.  

Armando Fox, John DeNero, and Kathy Yelick named CDSS associate deans

Three EECS faculty have been named associate deans for the Division of Computing, Data Science, and Society (CDSS).  CS Prof. Armando Fox is the associate dean of online programs; CS Prof. John DeNero is the associate dean of undergraduate studies; and EE Prof. Katherine Yelick is transitioning from her role as CDSS’s associate dean for research to the CDSS executive associate dean.  Berkeley launched CDSS in 2018 to expand teaching and research in data science, and to bring together programs, schools, and departments across campus to tackle the technical, scientific, social, and human dimensions of urgent challenges in biomedicine and human health, climate and sustainability, and human welfare and social justice.

Bin Yu awarded Honorary Doctorate from the University of Lausanne

CS Prof. Bin Yu has been awarded an Honorary Doctorate from the University of Lausanne, Switzerland (UNIL).  Honoris causa doctorates are often conferred as a way of recognizing individuals who are unaffiliated with an institution but who have contributed to a specific field or to society in general.  Yu was cited as "one of the most influential researchers of her time" for her "international reputation," "her character and her openness to others and to the world," and "the breadth and importance of her contributions" which "are far from being confined to the scientific community" and "are part of collective efforts to build a better world."  These include her recent work predicting the severity of COVID-19 in the United States.  Yu has a shared appointment in the Department of Statistics, and is affiliated with the Berkeley Institute for Data Science (BIDS) and the Berkeley Center for Computational Biology.

Ken Goldberg: Professor and Artist

CS/IEOR/Art Practice Prof. Ken Goldberg, who is also affiliated with Radiation Oncology at UCSF, is the subject of an interview with Ron Latanision and Cameron Fletcher for the National Academy of Engineering. Goldberg discusses the relationship between art and science in Western culture, the dual nature of his career trajectory, his passion for robot-related art, and why he is optimistic about the future of technology.  He also describes some of his projects, including the Telegarden installation, the African Robotics Network, and his Emmy-nominated film collaboration "Why We Love Robots."

Stuart Russell named Officer of the Most Excellent Order of the British Empire

CS Prof. Stuart Russell, has been named a 2021 Officer of the Most Excellent Order of the British Empire (OBE).  The Officer rank is the second of the order, and is bestowed by the Sovereign of the United Kingdom twice a year to reward valuable "services rendered to the United Kingdom and its people."  Russell, who co-authored the world's most popular AI textbook, Artificial Intelligence: A Modern Approach, and founded the Berkeley Center for Human-Compatible Artificial Intelligence (CHAI), was cited for "For services to artificial intelligence research."  He is an innovator in probabilistic knowledge representation, reasoning, and learning, including its application to global seismic monitoring for the Comprehensive Nuclear-Test-Ban Treaty.  He is also a powerful advocate for the creation of "safe AI" and is active in the movement to ban the manufacture and use of autonomous weapons.  His official title is now: Professor Stuart Russell OBE.

Jonathan Ragan-Kelley wins ACM SIGGRAPH 2021 Significant New Researcher Award

EECS Assistant Prof. Jonathan Ragan-Kelley is the recipient of the Association for Computing Machinery (ACM) Special Interest Group on Computer Graphics and Interactive Techniques (SIGGRAPH) 2021 Significant New Researcher Award.  The award honors researchers who are new to the field of computer graphics and who have made "recent, significant contributions to the field."  Ragan-Kelley, who was instrumental in the development of the language and compiler Halide, was cited for “outstanding contributions to systems and compilers in rendering and computational photography.” Halide is now the industry standard for providing fast, efficient and portable computation on images and tensors.  Ragan-Kelley is also an Assistant EECS professor at MIT.

Five projects led by EECS faculty win AI for Energy and Climate Security Awards

Five projects led by EECS faculty have won C3.ai Digital Transformation Institute (DTI) AI for Energy and Climate Security Awards. The awards recognize projects that are using AI techniques and digital transformation to advance energy efficiency and lead the way to a lower-carbon, higher-efficiency economy that will ensure energy and climate security.  "C3.ai DTI selects research proposals that inspire cooperative research and advance machine learning and other AI subdisciplines. Projects are peer-reviewed on the basis of scientific merit, prior accomplishments of the principal investigator and co-principal investigators, the use of AI, machine learning, data analytics, and cloud computing in the research project, and the suitability for testing the methods at scale." Each project was awarded $100,000 to $250,000, for an initial period of one year.  The winning proposals were:

Offline Reinforcement Learning for Energy-Efficient Power GridsSergey Levine, Assistant Professor, Electrical Engineering and Computer Sciences
We propose to develop offline RL algorithms to incorporate real-world data in training an RL agent to reduce emissions associated with running an electrical grid.

Sharing Mobile Energy Storage: Platforms and Learning Algorithms - Kameshwar Poolla, Cadence Design Systems Distinguished Professor of Mechanical Engineering
This proposal aims to design, validate, and test platforms and learning algorithms for mobile storage applications, which can simultaneously serve the role of generation (supplying energy) and distribution (reticulating energy).

Reinforcement Learning for a Resilient Electric Power SystemAlberto Sangiovanni-Vincentelli, Edgar L. and Harold H. Buttner Chair of Electrical Engineering and Computer Science
Harnessing the potential of AI techniques to make the power system resilient against such extreme cases is crucial. We propose to develop AI-based methods, and corresponding testing strategies, to achieve this goal.

Affordable Gigaton-Scale Carbon Sequestration: Navigating Autonomous Seaweed Growth Platforms by Leveraging Complex Ocean Currents and Machine LearningClaire Tomlin, Charles A. Desoer Chair in the College of Engineering
A promising approach to carbon sequestration utilizes seaweed, which fixates dissolved CO2 into biomass. Floating platforms that autonomously grow and deposit seaweed could scale this natural process to the open ocean, where the carbon is confined for millennia.

Interpretable Machine Learning Models to Improve Forecasting of Extreme-Weather-Causing Tropical Monster Storms - Da Yang, Faculty Scientist, Lawrence Berkeley National Laboratory, and Bin Yu, Chancellor's Distinguished Professor and Class of 1936 Second Chair Departments of Statistics and Electrical Engineering and Computer Sciences
We propose to develop interpretable, machine-learning (ML) models to forecast the Madden-Julian Oscillation (MJO) — the Storm King in Earth’s tropics.

Jennifer Chayes wins 2020 ACM Distinguished Service Award

CS Prof. Jennifer Chayes, who is also the Associate Provost for the Division of Computing, Data Science, and Society (CDSS), is the recipient of the 2020 Association for Computing Machinery (ACM) Distinguished Service Award.  She was selected for the award, which recognizes outstanding career-long "contributions to the computing community at large," for "her effective leadership, mentorship, and dedication to diversity during her distinguished career of computer science research, teaching, and institution building."  Chayes' contributions include leadership at both Microsoft Research (where she founded and led the Theory Group, and Microsoft Research New England, New York City and Montreal) and UC Berkeley (where she is also the Dean of the School of Information); service to many computing and science organizations (including the National Academy of Sciences, the National Research Council, and the ACM A.M. Turing Award Committee); expanding the diversity of the computing field through mentorship of women, underrepresented racial minorities and other disadvantaged groups; and making important research contributions in machine learning.