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Girish Pahwa wins 2022 IEEE EDS Early Career Award

Girish Pahwa has won the 2022 IEEE Electron Device Society (EDS) Early Career Award. Dr. Pahwa is an assistant professional researcher at Berkeley EECS and is currently the executive director of the Berkeley Device Modeling Center (BDMC), whose leadership includes EE Profs. Chenming Hu and Sayeef Salahuddin. His research interests include device modeling, simulation, and benchmarking of emerging nanoscale technologies. Awarded annually, the EDS Early Career Award recognizes and supports technical development within the EDS field of interest. Recipients are given a plaque and a check for $1,000 at the EDS Awards Dinner, held in conjunction with the international Electron Devices Meeting (IEDM), which will be held in San Francisco, CA this year.

Prof. Bayen points to traffic congestion that has been smoothed by CIRCLES vehicles on an I-24 MOTION testbed monitor.

Alexandre Bayen leads massive AI traffic experiment

An interdisciplinary team of industry and academic researchers led by EECS Prof. Alexandre Bayen has completed its most ambitious real-time traffic experiment to date. The project was led by the CIRCLES Consortium, an effort led by UC Berkeley and Vanderbilt University, involving collaborators from five universities and multiple government agencies. The experiment tested 100 partially automated vehicles in real traffic with the aim of improving overall traffic flow. Operating out of a massive control center designed to monitor one section of I-14 in Nashville, TN, the researchers used AI to build on existing adaptive cruise control systems to smooth phantom jams collaboratively. Their results show a positive energy impact. “Driving is very intuitive. If there’s a gap in front of you, you accelerate. If someone brakes, you slow down. But it turns out that this very normal reaction can lead to stop-and-go traffic and energy inefficiency,” said Prof. Bayen. “That’s precisely what AI technology is able to fix—it can direct the vehicle to things that are not intuitive to humans, but are overall more efficient.” 

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Raluca Ada Popa featured in People of ACM

CS Prof. Raluca Ada Popa was interviewed as a Featured ACM Member as part of the "People of ACM" bulletin. As the Co-Director of RISELab and SkyLab, two labs aiming to build secure intelligent systems for the cloud and for the sky of cloud, she spoke about her research interests, which include security, systems, and applied cryptography. “I love both to build systems that can solve a real-world problem and to reason about deep mathematical concepts,” she said. Aiming to predict the direction of her research, she outlined her renewed focus on confidential computing, a major shift in the cloud computing landscape, which she said “will revolutionize data systems in industry in the coming years…[through] the combination of hardware security via hardware enclaves and cryptographic techniques. Many organizations have a lot of confidential data that they cannot share between different teams in their organization or different organizations. Sharing it would enable better medical studies, better fraud detection, increased business effectiveness, and other benefits.”

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New institute combines machine learning and chemistry to tackle climate change

The Bakar Institute of Digital Materials for the Planet (BIDMaP), led by Chemistry Prof. Omar M. Yaghi, brings together CS Profs. Christian Borgs, Joseph Gonzalez, Jennifer Listgarten, Jennifer Chayes, and Kathy Yelick, along with faculty from the Department of Chemistry and Statistics, respectively, to affect climate change by combining machine learning and chemistry. The institute aims to develop a new field of machine learning for experimental science, creating algorithms and designing platforms to optimize the discovery, development, and deployment of technology. “This is what we need to accelerate discovery at a rate that will save us from the worst effects of climate change,” said Jennifer Chayes, EECS prof., associate provost for CDSS and dean of the School of Information. “BIDMaP will bring together the founder of an important new field in chemistry and the best artificial intelligence and machine learning group in the world to imagine and create a better future.”

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Pieter Abbeel interviewed as Featured ACM Member

CS Prof. Pieter Abbeel has been interviewed as a Featured ACM Member. As part of the “People of ACM” bulletin, Abbeel details the groundbreaking work that led to his 2021 ACM Prize in Computing, and the direction of the field of AI and robotics in the warehousing industry and beyond. Given the different specializations required to pursue AI, he gives the following advice to the next generation of AI researchers: “In terms of foundations, basic mathematics such as calculus, probability, linear algebra are very important, and also optimization,” said Abbeel. “Taking physics classes can be very helpful, as it teaches you the skill of abstracting real world problem settings into equations." Prof. Abbeel is the director of the Berkeley Robot Learning Lab and co-director of the Berkeley Artificial Intelligence Research (BAIR) lab, in addition to Co-Founder, President, and Chief Scientist of Covariant, a Berkeley-based AI robotics company.

BAIR Climate Initiative creates partnerships to fight climate change

Berkeley Artificial Intelligence researchers are joining forces with climate experts, government agencies, and industry, as part of the new Berkeley AI Research (BAIR) Climate Initiative, a multi-disciplinary student-led hub dedicated to fighting climate change.  The effort is being led by co-founding director CS Prof. Trevor Darrel and organized by three of his graduate students, Colorado Reed (co-advised by Kurt Keutzer), who will help lead the initiative, Medhini Narasimhan, and Ritwik Gupta (co-advised by Shankar Sastry).  Their objective is to develop AI techniques that address problems with data processing, particularly involving massive data sets. To maximize the benefit to other researchers studying the same problems around the world, all work done by the initiative will be openly published and available without exclusive or proprietary licensing.  One of their first projects, “The Fate of Snow,” will be a collaboration between BAIR Climate Initiative researchers and other scientists and policy experts on the Berkeley campus, Berkeley Lab (LBNL), Meta AI (which belongs to Meta Platforms, Inc.) and the Center for Western Weather and Water Extremes. The researchers plan to apply AI methods to a multitude of openly available weather and satellite data sources to estimate how much water is in the Sierra Nevada snowpack and forecast what that will mean for streadmflow in the region.

New Sky Computing Lab aims to revolutionize the cloud industry

Sky Computing Lab, the latest 5-year collaborative research lab launched out of Berkeley EECS, aims to build a new backbone for interconnected cloud computing, a milestone that would revolutionize the industry. The lab will leverage distributed systems, programming languages, security, and machine learning to decouple the services that companies want to implement from the choice of a specific cloud, with the goal of transforming the cloud into an undifferentiated commodity, much like the Internet. Google, IBM, Intel, Samsung SDS, and VMware are among the founding sponsors of the lab. The lab's team is comprised of over 60 members, including students, staff, and EECS faculty like Alvin Cheung, Natacha Crooks, Ken Goldberg, Joseph Gonzalez, Joe Hellerstein, Mike Jordan,  Anthony Joseph, Raluca Ada Popa, Koushik Sen, Scott Shenker, and Dawn Song. CS Prof. Ion Stoica, who will lead the lab, says “Sky will knock out current barriers and accelerate the transition to the cloud, which will accelerate the progress across different fields.”

 

Kam Lau wins Caltech Distinguished Alumni Award

EECS Prof. Emeritus Kam Lau, has won the 2022 California Institute of Technology Distinguished Alumni Award, the highest honor presented by Caltech to its alumni.  He was cited "for extraordinary contributions to society as an engineer, entrepreneur, and artist." Lau is known for his pioneering developments and commercialization of RF over fiber devices, systems and applications, which helped launch the microwave photonics industry.  He received his B.S., M.S., and Ph.D degrees from Caltech in 1978, 1978 and 1981, respectively.  Before coming to Berkeley in 1990, he was founding chief scientist of Ortel Corporation, and a professor at Columbia University.  He subsequently  co-founded LGC Wireless with some of his Berkeley colleagues.  Lau is also an accomplished ink painting artist.  At age 16, his work was accepted into the 1972 Hong Kong Contemporary Art Exhibition, a venue for professional artists, and one of his pieces was acquired by the Hong Kong Museum of Art for its permanent collection.

Pravin Varaiya wins 2022 IEEE Simon Ramo Medal

EECS Prof. Emeritus and alumnus Pravin Varaiya (Ph.D. 1966, advisor: Lotfi Zadeh), who is currently a Professor in the Graduate School, has won the 2022 IEEE Simon Ramo Medal.  This major IEEE Corporate Award recognizes "exceptional achievement in systems engineering and systems science." Varaiya, who is known for his contributions to stochastic control, hybrid systems and the unification of theories of control and computation, was cited “for seminal contributions to the engineering, analysis, and design of complex energy, transportation, and communication systems.”

New AI system allows legged robots to navigate unfamiliar terrain in real time

A new AI system, Rapid Motor Adaptation (RMA), enhances the ability of legged robots, without prior experience or calibration, to adapt to, and traverse, unfamiliar terrain in real time.  A test robot figured out how to walk on sand, mud, and tall grass, as well as piles of dirt, pebbles, and cement, in fractions of a second.  The project is part of an industry-academic collaboration with the Facebook AI Research (FAIR) group and the Berkeley AI Research (BAIR) lab that includes CS Prof. Jitendra Malik as Principal Investigator, his grad student Ashish Kumar as lead author, and alumnus Deepak Pathak (Ph.D. 2019, advisors: Trevor Darrell and Alexei Efros), now an assistant professor at Carnegie Mellon, among others.  RMA combines a base policy algorithm that uses reinforcement learning to teach the robot how to control its body, with an adaptation module that teaches the robot how to react based on how its body moves when it interacts with a new environment.  “Computer simulations are unlikely to capture everything,” said Kumar. “Our RMA-enabled robot shows strong adaptation performance to previously unseen environments and learns this adaptation entirely by interacting with its surroundings and learning from experience. That is new.”  RMA's base policy and adaptation module run asynchronously and at different frequencies so that it can operate reliably on a small onboard computer.