A team of researchers from UCSF and Berkeley EECS have developed an implantable AI-powered device that can translate brain signals into modulated speech and facial expressions. The device, a multimodal speech prosthesis, and digital avatar, was developed to help a woman who had lost the ability to speak due to a stroke. The results have the potential to help countless others who are unable to speak due to paralysis or disease. The breakthrough study, published in the journal Nature, was led by UCSF neurosurgeon Edward Chang, EE Assistant Professor Gopala Anumanchipalli and Ph.D. student Kaylo Littlejohn. “This study heavily uses tools that we developed here at Berkeley, which in turn are inspired by the neuroscientific insights from UCSF,” said Gopala. “This is why Kaylo is such a key liaison between the engineering and the science and the medicine — he’s both involved in developing these tools and also deploying them in a clinical setting. I could not see this happening anywhere else but somewhere that is the best in engineering and the best in medicine, on the bleeding edge of research.”

Tsu-Jae King Liu’s leadership of the nation’s top public school of engineering is continuing for a second term. Chancellor Carol Christ and Executive Vice Chancellor and Provost Benjamin Hermalin announced on August 1st in a campus message that Liu has accepted her reappointment as dean of UC Berkeley’s College of Engineering. “We extend our sincere congratulations to Tsu-Jae on her reappointment, effective as of July 1, 2023,” they stated in a campus announcement. “Her exceptional leadership, vision and unwavering commitment to the college and to UC Berkeley have set a remarkable precedent, and we look forward to seeing Berkeley Engineering’s continued growth and success under her leadership and guidance.” King Liu is the Roy W. Carlson Distinguished Professorship in Engineering in EECS. Her research activities are presently in advanced materials, fabrication processes and devices for energy-efficient electronics. She has authored or co-authored over 500 publications and holds over 90 patents. Professor Liu is a Fellow of the IEEE and a member of the U.S. National Academy of Engineering and serves on the board of directors for Intel Corporation. “My goal is for Berkeley Engineering to exemplify excellence in all that we do to benefit people and society through innovation and collaboration,” said Liu. “I look forward with excitement to seeing all that we will accomplish together as a community in the years ahead.”

A team led by CS Assistant Professor Anjoo Kanazawa has created Nerfstudio, an open-source platform to help speed up the development of Neural Radiance Fields (NeRFs). NeRFs are a type of 3D imaging technology that can be used to create photorealistic 3D models of objects and scenes from a series of images. The plug-and-play framework, called Nerfstudio, makes it easier for researchers to create and train NeRFs, allowing users to run NeRFs on real-world data. “Advancements in NeRF have contributed to its growing popularity and use in applications such as computer vision, robotics, visual effects and gaming. But support for development has been lagging,” said Kanazawa. “The Nerfstudio framework is intended to simplify the development of custom NeRF methods, the processing of real-world data and interacting with reconstructions.”

CS Professor Stuart Russell testified before the U.S. Senate Committee on Commerce, Science, and Transportation about the regulation of artificial intelligence (AI). In the July 25 hearing, Russell argued that AI is a powerful technology that has the potential to do great good or great harm, and he urged the Senate to take a proactive approach to regulating AI. Russell's testimony focused on three key areas of AI regulation: transparency, accountability, and safety. “My research over the last decade has focused on the problem of control: how do we maintain power, forever, over entities that will eventually become more powerful than us? How do we ensure that AI systems are safe and beneficial for humans? These are not purely technological questions. In both the short term and the long term, regulation has a huge role to play in answering them,” said Russell.

EE Professor Venkat Anantharam and Chinese University of Hong Kong (CUHK) Professor Cheuk-Ting Li have won the 2023 IEEE Information Theory Society Paper Award. The award is given annually “for an outstanding publication in the fields of interest to the Society appearing anywhere during the preceding four calendar years.” The paper “A unified framework for one-shot achievability via the Poisson matching lemma,” by Li and Anantharam, appeared in the IEEE Transactions on Information Theory in February 2021, when Li was a postdoctoral fellow at Berkeley EECS. Li is now an assistant professor at the CUHK. Anantharam, who is an IEEE Fellow, received this award once before in 2008 for the paper “Bits Through Queues.”

CS Professor Alyosha Efros has won the Thomas S. Huang Memorial Prize. The Huang Memorial Prize was established in 2020 by IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI). The prize, which is awarded annually at the IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR), recognizes exemplary research, teaching, mentoring, and service to the computer vision community. Thomas S. Huang was a pioneering scholar “who left deep impressions in multiple fields including computer vision and image processing, and a role model who contributed to the growth and well-being of several generations of researchers in the community.” The award includes a cash prize of $3,000 and a commemorative plaque.

A team led by CS Professor Shafi Goldwasser has won the 2023 Edsger W. Dijkstra Prize in Distributed Computing. The 1988 paper, "Completeness Theorems for Non-Cryptographic Fault-Tolerant Distributed Computation," by Michael Ben-Or, Shafi Goldwasser, and Avi Wigderson was among the three papers to receive the award. Awarded annually, the Dijkstra Prize, which is jointly sponsored by the ACM Symposium on Principles of Distributed Computing (PODC) and the EATCS Symposium on Distributed Computing (DISC), recognizes papers whose significance and impact on the theory and practice of distributed computing has been evident for at least 10 years. The prize includes an award of $2,000. Shafi Goldwasser is the director of the Simons Institute for the Theory of Computing. She is a member of the National Academy of Engineering, the National Academy of Sciences, and the American Academy of Arts and Sciences. She received the Turing Award in 2012.

CS Teaching Professor Dan Garcia has joined the board of directors of The Computing Research Association’s Committee on Widening Participation in Computing Research (CRA-WP). The CRA-WP was established in 1991 with the goal of increasing the participation of women in computing research, though its current mission broadly supports underrepresented populations to improve access, opportunities, and experiences of those in computing research and higher education.

CS Assistant Professors Sophia Shao and Nika Haghtalab have won Google Research Scholar Awards. The Google Research Scholar Program provides financial support for world-class research conducted by professors in the early stage of their academic careers. Shao’s research interests include computer architecture, focusing on specialized accelerators, heterogeneous architecture, and agile VLSI design methodology. Haghtalab’s research interests include machine learning, algorithms, economics, and society, contributing to an emerging mathematical foundation for learning and decision-making systems in the presence of economic and societal forces.

An article produced by the College of Computing, Data Science, and Society highlighted the increasingly frought landscape of user privacy in the emerging world of Virtual Reality (VR) devices. The article cites two papers published by faculty, students, and visitors affiliated with the Berkeley Center for Responsible, Decentralized Intelligence. Led by CS Ph.D student Vivek Nair and Professor Dawn Song, the research showed that users of such devices can be identified using just minutes of their head and hand movements. Movement data, which is collected and shared with companies and other players to fuel these worlds, can be used to infer dozens of details from age to disability status. One paper demonstrates that body movements are as singular and reliable an identifier as fingerprints, which was accepted for publication at the USENIX Security Symposium. Another found that use of headset data could accurately identify or infer more than 25 characteristics, including location, age and height, which will be published for the Privacy Enhancing Technologies Symposium. “We've done an extensive job of proving that there is a privacy risk here and that it is a different kind of privacy risk than what we have seen on the web,” Nair said. “These kinds of approaches for how to either transform the data or control who has access to it, that's going to be our main focus moving forward." Berkeley RDI is a multi-disciplinary initiative aimed at advancing the science, technology and education of decentralization and empowering a responsible digital economy. This work is part of the center’s Metaverse security and privacy research effort.