EECS Associate Prof. Boubacar Kanté is among the authors of a paper published in the journal Science titled "Plasmonic topological metasurface by encircling an exceptional point."  The paper introduces "an additional degree of freedom to address optical phase engineering by exploiting the topological features of non-Hermitian matrices operating near [the] singular points".   The novel phase, which was shown to be topologically protected, enables the construction of novel polarization dependent and chiral phased arrays and holograms. The ease of implementation together with its compatibility with other phase-addressing mechanisms will enable information multiplexing with antenna arrays.

CS Prof. Joseph Hellerstein, and Assistant Profs. Aditya Parmeswaran and Sarah Chasins, are among the principal investigators of a new lab that has just received a $2M grant from the National Science Foundation to make big datasets used by the criminal justice system more accessible to non-technical researchers.  The Effective Programming, Interaction, and Computation with Data (EPIC) Lab will create tools that utilize machine learning, program synthesis, and human-centered design, to improve the ability of public defenders, investigators and paralegals to research police misconduct, judicial decision-making, and related issues, for their cases.  The tools, which will initially be used in San Francisco, Alameda and Sacramento, are designed to address systemic power and resource disparities in California by helping under-resourced practitioners better defend their clients.

EECS Assistant Prof. Gopala Anumanchipalli has been selected for the Rose Hills Innovator Program which supports distinguished early-career UC Berkley faculty who are "interested in developing highly innovative research programs" in STEM fields.  The program will provide discretionary research support of up to $85,000 per year for "projects with an exceptionally high scientific promise that may generate significant follow-on funding."   Anumanchipalli's project, titled "Multimodal Intelligent Interfaces for Assistive Communication," proposes to "improve the current state of assistive communication technologies by integrating multiple neural and behavioral sensing modalities, and tightly integrating the graphical interfaces, and personalizing them to the user’s context."  His team will use "state-of-the-art neural engineering and artificial intelligence to develop novel communication interfaces" including Electrocorticography, non-invsive in-ear Electroencephalography sensors and functional near infrared spectroscopy.  They will also use on-device speech recognition and dialog management to incorporate the acoustic context of the user.

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.

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.

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."

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.