EECS Prof. Pieter Abbeel launched “The Robot Brains Podcast” in the spring of 2021. In each episode, he is joined by leading experts in AI Robotics from around the world to explore how far humanity has come in its mission to create conscious computers, mindful machines and rational robots. Abbeel sits down for a Q&A with Berkeley Engineering, in which he discusses his experience with podcasting and how it has shaped his own thinking about communicating AI to a broader audience.
A new type of high-resolution LiDAR chip developed by EECS Prof. Ming Wu could lead to a new generation of powerful, low-cost 3D sensors for autonomous cars, drones, robots, and smartphones. The paper, which appeared in the journal Nature, was co-authored by his former graduate students Xiaosheng Zhang (Ph.D. '21) and Johannes Henriksson (Ph.D. '21), current graduate student Jianheng Luo, and postdoc Kyungmok Kwon, in the Berkeley Sensor and Actuator Center (BSAC). Their new, smaller, more efficient, and less expensive LiDAR design is based on a focal plane switch array (FPSA) with a resolution of 16,384 pixels per 1-centimeter square chip, which dwarfs the 512 pixels or less currently found on FPSA. The design is scalable to megapixel sizes using the same complementary metal-oxide-semiconductor (CMOS) technology used to produce computer processors. Additionally, large, slow and inefficient thermo-optic switches are replaced by microelectromechanical system (MEMS) switches, which are traditionally used to route light in communications networks. If the resolution and range of the new system can be improved, conventional CMOS production technology can be used to produce the new, inexpensive chip-sized LiDAR.
CS graduate student Chandan Singh (advisor: Bin Yu) has made it to the semi-finals of the 2022 Berkeley Grad Slam Competition, a UC showcase for graduate student research presented in three-minute talks for a general audience, likened to short Ted Talks. In "Unlocking Scientific Secrets by Distilling Neural Networks," Singh hopes to build on recent advances in machine learning to improve the world of healthcare. His research focuses on how to build trustworthy machine-learning systems by making them more interpretable through partnerships with domain experts (e.g. medical doctors and cell biologists). These collaborations give rise to useful methodology that both build more transparent models as well as improve the trustworthiness of black-box models. He hopes to help bridge the gap between both types of models so that they can be reliably used to improve real-world healthcare.
EECS and Bioengineering Prof. Steven Conolly has been awarded the 2022 U.C. Berkeley Bakar Prize. This prize is given annually to former Bakar Program Fellows whose technological innovations promise to deliver solutions to some of the world’s most pressing problems. Funds are provided to help new technologies transition from an academic setting to industrial applications. The objective of Conolly's project, titled Rapid in vivo optimization of solid tumor CAR-T cell therapies using advanced magnetic particle imaging (MPI), is to determine whether a particular CAR-T cell cancer immunotherapy is working in hours rather than months. CAR-T cells are tagged with safe magnetic nanoparticles before a treatment is administered so that oncologists can view how well they are targeting cancer cells using high resolution imaging technology.
EE alumnus Colin Parris (M.S. '87, Ph.D. '94, advisor: Domenico Ferrari) has been elected to the National Academy of Engineering (NAE). After a career at IBM Systems & Technology and General Electric (GE) Research, Parris is currently Senior Vice President and Chief Technology Officer at GE. He is known for his life-long commitment to "the development and enhancement of STEM programs across minority communities," and serves as a board member of the Annual Multicultural Business Youth Educational Services Embarkment (Ambyese), which prepares multicultural secondary school students for the challenges of pursuing careers in the corporate sector through self-esteem-building and exposure to successful role models in industry. While a student Berkeley, Parris helped start the Summer Undergraduate Program in Engineering Research at Berkeley (SUPERB) and was deeply involved with the group Black Graduate Engineering and Science Students (BGESS). At GE, Parris, whose expertise spans engineering, software, and AI-driven analytics, leads teams that leverage digital technologies in the energy industry and other industrial environments. He created and leads the Digital Twin Initiative company-wide and is currently working to "accelerate business impact and transformation by combining lean principles with digital solutions."
EECS Prof. Katherine Yelick has won the 2022 CRA Distinguished Service Award. This award recognizes "a person or organization that has made an outstanding service contribution" with a major impact "to the computing research community" in the areas of government, professional societies, publications, conferences, or leadership. Yelick has been a professor in the department since 1991, and was the Associate Laboratory Director for Computing Sciences at Lawrence Berkeley National Laboratory (LBNL). She is known as the co-inventor of the UPC and Titanium languages and demonstrated their applicability through the use of novel runtime and compilation methods. She also co-developed techniques for self-tuning numerical libraries. She is the co-author of two books and more than 100 refereed technical papers on parallel languages, compilers, algorithms, libraries, architecture, and storage.
CS Assistant Prof. Avishay Tal has been selected as a 2022 Alfred P. Sloan Research Fellow in Computer Science. This award recognizes outstanding early-career faculty for their "potential to revolutionize their fields of study." Tal is a member of the Theory group; his interests include computational complexity, analysis of boolean functions, circuit and formula lower bounds, query complexity, pseudorandomness, computational learning theory, quantum computing, combinatorics, and connections between algorithms and lower bounds. He is among 4 winners from UC Berkeley representing the fields of CS, math, physics, and neuroscience. Winners receive $75K, which may be spent over a two-year term to support their research.
Researchers from the Pilawa Research Group, including EECS alumnus Nathan Pallo (Ph.D. '21), EECS Associate Prof. Robert Pilawa-Podgurski, and former postdoc Tomas Modeer, have won one of four 1st place 2020 IEEE Power Electronics Society (PELS) Transactions Prize Paper Awards. Their paper, which was co-authored by Pilawa-Podgurski's UIUC graduate students, Tom Foulkes and Chris Barth, is titled "Design of a GaN-Based Interleaved Nine-Level Flying Capacitor Multilevel Inverter for Electric Aircraft Applications." This award is considered the top publication award in the field of power electronics, and is known for it's rigorous evaluation process, which recognizes "originality; contribution to the field; extent to which the paper is supported by analysis and experimental evidence; and quality of presentation, including the effective use of illustrations." The winners of the 2020 award were selected from a pool of 1,148 papers.
Students in the Data Science Discovery Program are filling a gap in engineering resources to help journalists more easily sort through large stores of records for their research. The Discovery Program, which is part of Berkeley's Division of Computing, Data Science, and Society (CDSS), connects around 200 undergraduates with hands-on, team-based data science research projects at Berkeley, government agencies, community groups, and entrepreneurial ventures. Students have worked on projects like the SF Chronicle's air quality map, the Wall Street Journal's effort to analyze its source and topic diversity using natural processing language, and the California Reporting Project's police misconduct database. “I don’t know if we’d be able to do this without them,” said KQED data reporter Lisa Pickoff-White. “None of these newsrooms would be able to automate this work on their own.”
EECS Associate Prof. Aditya Parameswaran has been selected to receive the Young Alumni Achievers Award from the Indian Institute of Technology (IIT), Bombay. This award "recognizes and celebrates the outstanding achievements of [IIT's] young alumni in their chosen field of endeavor." Parameswaran, who has a joint appointment at the I School, synthesizes techniques from data systems and human-computer interaction to develop tools to simplify data science at scale. His tools, which have been downloaded and employed by millions of users, empower "individuals and teams to leverage and make sense of their large datasets more easily, efficiently, and effectively." These include the Lux library, an intelligent visualization recommendation system for very large data sets in dataframe workflows, and Modin, a scalable dataframe system which applies database and distributed systems ideas to help run dataframe workloads faster. The award will be presented during the university's Institute Foundation Day Function on March 10, 2022.
