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.
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.
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 Grids - Sergey 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 System - Alberto 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 Learning - Claire 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.
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.
EECS Prof. S. Shankar Sastry has won the 2021 American Society of Mechanical Engineers (ASME) Rufus Oldenburger Medal for significant contributions and outstanding achievements to the field and profession of automatic control. Sastry, who was dean of Berkeley Engineering for over ten years, was cited “For fundamental contributions to the foundations of nonlinear, adaptive and hybrid control, control of robots and vehicles, and for contributions to control and robotics education.” EECS Prof. Lotfi Zadeh (1921-2017) previously won this award in 1993. The medal will be presented at the ASME Dynamic Systems and Control Division Awards ceremony and dinner, which will take place at the newly instituted Modeling, Estimation and Control Conference (MECC 2021), in Texas in October.
A team at the Berkeley Natural Language Processing Group (NLP) helped augment an AI system named "Dr. Fill" that has won the 2021 American Crossword Puzzle Tournament (ACPT). This is the first time in the contest's history that an AI has trumped its human competitors. The team, which included CS Prof. Dan Klein, graduate students Nicholas Tomlin, Eric Wallace, and Kevin Yang, and undergraduate students Albert Xu and Eshaan Pathak, approached Matthew Ginsberg, who created the Dr. Fill algorithm in 2012, and offered to join forces by contributing their machine learning system called the Berkeley Crossword Solver (BCS). BCS employs a neural network model to combine general language understanding with more "creative" crossword puzzle clues, then applies its knowledge to practice puzzles, improving as it learns. “We had a state-of-the-art natural language understanding and question-answering component but a pretty basic crossword handler, while Matt had the best crossword system around and a bunch of domain expertise, so it was natural to join forces,” said Klein. “As we talked, we realized that our systems were designed in a way that made it very easy to interoperate because they both speak the language of probabilities.” ACPT is the oldest and biggest tournament of its kind, consisting of seven qualifying puzzles and a final playoff puzzle; solvers are ranked using a formula that balances accuracy and speed. Although Dr. Fill made three errors, it completed most puzzles in well under a minute, and ultimately outscored its top human competitor, who made zero errors, by 15 points. The contest was held online this year and attracted more than 1,100 contestants vying for the $3K grand prize.
Dean of Berkeley Engineering and EECS Prof. Tsu-Jae King Liu, and EECS Profs. Emeritus Leon Chua and Chenming Hu (also Professor in the Graduate School), are featured as luminaries in an IEEE Electron Devices Society (EDS) Podcast Series. Considered among "the most successful members of the [Electron Devices] Society," these three professors share their insights and wisdom in interviews designed to provide "invaluable inspiration and knowledge for those in the engineering field." Liu, the first and only woman to chair the EECS Department, leads a research team that explores the development of novel semiconductor devices, non-volatile memory devices, and M/NEMS technology for ultra-low power circuits. Hu is considered a “microelectronics visionary" whose seminal work on metal-oxide semiconductor MOS reliability and device modeling has had enormous impact on the continued scaling of electronic devices. Chua is an expert in nonlinear circuit theory and cellular neural network theory, the inventor of the eponymous Chua's circuit, and the first person to postulate the existence of the memristor. Liu and Hu are among the co-inventors of the three-dimensional FinFET transistor, which is used in all leading microprocessor chips today.
EE graduate student Charles Dove (advisor: Laura Waller) has been named a 2021 Fellow by the Fannie and John Hertz Foundation, a nonprofit organization dedicated to advancing groundbreaking applied science with real-world benefits for all humanity. Dove utilizes principles from machine learning and differentiable programming to create new methods for the simulation and fully automatic design of light-based technology. This capability would enable significant growth in the scale, scope, and capabilities of nearly all light-based technology, including biomedical imaging, cellular manipulation and characterization, optical telecommunications, photonic quantum computing, and LIDAR. Hertz Foundation awards allow fellows "the freedom to pursue innovative research wherever it may lead."
CS Prof. Mike Jordan has been elected a Foreign Member of the Royal Society. The Royal Society began as an "'invisible college' of natural philosophers and physicians," which opened its first meeting in 1660 with a lecture by acclaimed scientist Christopher Wren. Their mission is "to recognise, promote, and support excellence in science and to encourage the development and use of science for the benefit of humanity." Jordan joins an elite group of 8,000 Fellows elected over the past 400 years that includes Isaac Newton (1672), Charles Darwin (1839), Albert Einstein (1921), Stephen Hawking (1974), and EECS Prof. Eli Yablonovitch (2013). Fellows and Foreign members must be nominated by at least two Fellows of the Royal Society, and must have made "a substantial contribution to the improvement of natural knowledge, including mathematics, engineering science and medical science." Jordan is known as one of the leading figures in machine learning, and one of the world's most influential computer scientists. New Fellows are formally admitted to the Society at the Admission Day ceremony in July, when they sign the Charter Book and the Obligation of the Fellows of the Royal Society.
A paper co-authored by Berkeley EECS Prof. Jeffrey Bokor, his postdoc Yuxuan Lin, Berkeley Physics Prof. Alex Zettl, his postdoc Cong Su, and researchers at MIT, among others, describes a more efficient method of connecting atomically thin 2-D materials to other chip elements, making them a more promising alternative to 3-D silicon-based transistors. The paper, which was published in Nature, is titled "Ultralow contact resistance between semimetal and monolayer semiconductors." It describes how using the element bismuth (in the place of ordinary metals) for connections in monolayer materials can create contact resistances that approach the quantum limit and make it possible to develop smaller devices. “We resolved one of the biggest problems in miniaturizing semiconductor devices, the contact resistance between a metal electrode and a monolayer semiconductor material,” says Su. "Through this approach," the paper states, "we achieve zero Schottky barrier height, a contact resistance of 123 ohm micrometres and an on-state current density of 1,135 microamps per micrometre on monolayer MoS2; these two values are, to the best of our knowledge, the lowest and highest yet recorded, respectively."
