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.”

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.”

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.

Professor Joseph Hellerstein was awarded the 2023 SIGMOD Edgar F. Codd Innovations Award, citing innovative contributions in extensible query processing, interactive data analytics, and declarative approaches to networking and distributed computing. The award is given for innovative and highly significant contributions of enduring value to the development, understanding, or use of database systems and databases. Until 2003, this award was known as the “SIGMOD Innovations Award.” In 2004, SIGMOD, with the unanimous approval of ACM Council, decided to rename the award to honor Dr. E.F. (Ted) Codd (1923 – 2003) who invented the relational data model and was responsible for the significant development of the database field as a scientific discipline. SIGMOD, otherwise known as the the ACM Special Interest Group on Management of Data, is concerned with the principles, techniques and applications of database management systems and data management technology. Its members include software developers, academic and industrial researchers, practitioners, users, and students. SIGMOD sponsors the annual SIGMOD/PODS conference, one of the most important and selective in the field.

EECS Assistant Professor Alane Suhr has received an honorable mention for the 2022 ACM Doctoral Dissertation Award. Suhr’s dissertation, “Reasoning and Learning in Interactive Natural Language Systems,” was honored “for formulating and designing algorithms for continual language learning in collaborative interactions, and designing methods to reason about context-dependent language meaning.” Suhr’s research is focused on natural language processing, machine learning, and computer vision. Suhr will be joining Berkeley EECS as an assistant professor in July 2023.

The U.S. News & World Report ranked both the Electrical Engineering and Computer Science graduate programs at Berkeley EECS among the top three graduate programs in the nation for 2023. Computer Science is ranked #1, tied with MIT and Stanford. Electrical Engineering and Computer Engineering are ranked #2, tied with Stanford. The magazine based its rankings on responses from 202 engineering schools across the country, including data from fall 2022 and early 2023. This year, U.S. News included non-responders from the 220 schools surveyed, so long as they reported enough data to be eligible in 2022.

Two proposals led by CS Assistant Teaching Professor Narges Nourozi have won $4M in funding from the National Science Foundation Directorate for Computer and Information Science and Engineering (CISE) and Directorate for STEM Education (EDU). The proposals, “Transforming Introductory Computer Science Instruction with an AI-Driven Classroom Assistant” and “CUE-P: Establishing Servingness in Computing through Baskin Engineering Excellence Scholars Program” have been awarded approximately $2M over four years, and $1.93M over five years, respectively. The first proposal, INSIGHT, is a collaboration between North Carolina State University and UC Berkeley focusing on an AI-driven classroom assistant that holds significant transformative potential for yielding a deeper understanding of how students learn computer science with AI-driven classroom assistants and producing a set of practical instructional support principles for coding-enriched classroom interactions. The second proposal is a CUE Pathways project, wherein researchers from the Universities of California collaborate with eight California community colleges to study the effects of operationalizing servingness and transfer pathways between two- and four-year institutions to increase persistence, knowledge attainment, belongingness, graduation, and post-graduation outcomes.

Alishba Imran, a 1st-year undergraduate student studying computer science, was named in Teen Vogue’s 21 under 21. The list recognizes those “who have made a substantial impact in both their communities and the world.” Imran, an undergraduate researcher in CS Prof. Ken Goldberg’s AUTOLab, focuses her work on using machine learning to solve real-world problems, like tracking counterfeit medication in the supply chain or using machine learning and physics to develop renewable energy storage devices. “I think the best things to work on are at the intersection of what you're good at, what you enjoy, and are a way for you to create value for the world,” said Imran.

CS Profs. Dawn Song and David Wagner have won the Association for Computing Machinery (ACM) Special Interest Group on Security, Audit and Control (SIGSAC) Test-of-Time Award. The 2011 paper titled, “Android Permissions Demystified,” by Felt, Chin, Hanna, Song and Wagner, was the first paper to examine real-world security issues in Android applications' use of permissions. The paper has been cited 1985 times and is still taught in graduate courses today. The award was presented at the ACM Conference on Computer and Communications Security (CCS), the flagship conference of the ACM SIGSAC, which took place in Los Angeles this year.