CS graduate student Sam Kumar (advisors: David Culler and Raluca Ada Popa) has won the Jay Lepreau Best Paper Award at the 15th USENIX Symposium on Operating Systems Design and Implementation (OSDI) for "MAGE: Nearly Zero-Cost Virtual Memory for Secure Computation." The OSDI, which brings together "professionals from academic and industrial backgrounds in a premier forum for discussing the design, implementation, and implications of systems software," selects three best papers each year after a double-blind review. Co-authored by Prof. David Culler and Associate Prof. Raluca Ada Popa, the paper introduces an execution engine for secure computation that efficiently runs computations that do not fit in memory. It demonstrates that in many cases, one can run secure computations that do not fit in memory at nearly the same speed as if the underlying machines had unbounded physical memory to fit the entire computation. Kumar works in the Buildings, Energy, and Transportation Systems (BETS) research group in the RISE Lab.
"PlushPal: Storytelling with Interactive Plush Toys and Machine Learning," co-authored by CS Masters student Deanna Gelosi (advisor: Dan Garcia), has won the Best Full Paper Award at the Association for Computing Machinery (ACM) Interaction Design for Children (IDC) conference 2021. IDC is "the premier international conference for researchers, educators and practitioners to share the latest research findings, innovative methodologies and new technologies in the areas of inclusive child-centered design, learning and interaction." The paper, which was presented in the "Physical Computing for Learning" conference session, describes PlushPal, "a web-based design tool for children to make plush toys interactive with machine learning (ML). With PlushPal, children attach micro:bit hardware to stuffed animals, design custom gestures for their toy, and build gesture-recognition ML models to trigger their own sounds." It creates "a novel design space for children to express their ideas using gesture, as well as a description of observed debugging practices, building on efforts to support children using ML to enhance creative play." Gelosi's degree will be in the field of Human-Computer Interaction and New Media, and her research interests include creativity support tools, traditional craft and computing technologies, digital fabrication, and equity in STEAM. She is a member of the Berkeley Center for New Media (BCNM), the Berkeley Institute of Design (BID), and the Tinkering Studio--an R&D lab in the San Francisco Exploratorium.
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.
CS Prof. Pieter Abbeel has won the 2022 IEEE Kiyo Tomiyasu Award, a prestigious Technical Field Award that recognizes "outstanding early to mid-career contributions to technologies holding the promise of innovative applications." Abbeel, who is the director of the Berkeley Robot Learning Lab, co-director of the Berkeley AI Research (BAIR) Lab, and co-founder of covariant.ai and Gradescope, was cited “For contributions to deep learning for robotics." His research focuses on teaching robots reinforcement learning through their own trial and error, apprenticeship learning from people, and met-learning (learning-to-learn) to speed up skill acquisition.
EE Prof. Emeritus Nelson Morgan has won the 2022 James L. Flanagan Speech and Audio Processing Award, a prestigious IEEE Technical Field Award. Morgan and co-recipient Herve Bourlard, who are known for their seminal work in the 1990s on a hybrid system approach to speech recognition that uses neural networks probabilistically with Hidden Markov Models, were cited for "contributions to neural networks for statistical speech recognition."
EECS Ph.D. students Kevin Cheang and Federico Mora (advisor: Sanjit A. Seshia) have been awarded a 2021 Qualcomm Innovation Fellowship (QiF) for their proposed project on "Practical Lifting for Verification of Trusted Platform Software." They are one of the sixteen winners of this year's QiF North America competition, which recognizes "innovative PhD students across a broad range of technical research areas, based on Qualcomm’s core values of innovation, execution and teamwork. QIF enables graduate students to be mentored by our engineers and supports them in their quest towards achieving their research goals."
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.
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 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.
