Pieter Abbeel, the co-founder, president and chief scientist of the start-up Covariant, is featured in a number of articles appearing in major publications this week.  The New York Times, the Wall Street Journal, Wired Magazine, the Verge, the MIT Technology Review, and the IEEE Spectrum all feature articles about robots trained using Covariant's AI technologies that will be deployed  to perform complex tasks in live warehouse environments in the next few years.  Covariant uses deep reinforcement learning techniques to train robots to distinguish between materials that are particularly difficult to discern through a lens, like highly reflective metallic surfaces, transparent plastics, and easily deformable surfaces like cloth and polypropylene, with an unparalleled 99% accuracy.

In celebration of the anniversary of 150 Years of Women at Berkeley (150W) in 2020, the EECS department will profile a number of remarkable women who have studied or worked here.  This month, Berkeley EECS is highlighting ten trailblazing women who were the first to reach important milestones over the past 50 years.  Learn how professors Susan Graham, Avideh Zakhor, Shafi Goldwasser and Tsu-Jae King Liu, and alumnae Kawthar Zaki, Carol Shaw, Paula Hawthorn, Barbara Simons, Deborah Estrin, and Susan Eggers, broke through glass ceilings on campus, in their fields, in industry, and in the world.

EECS Profs. Trevor Darrell, Anca Dragan, Ken Goldberg, Randy Katz and Stuart Russell are slated to participate in "TechCrunch Sessions: Robotics + AI 2020" on March 3rd.  The single-day event will focus on "Minds and Machines: The Future of Robotics," and will feature "on-stage, live interviews and demos with the world's leading technologists, founders and investors, as well as workshops, audience Q&A with speakers, and highly curated networking."  The event is sponsored by online publishing company TechCrunch in partnership with UC Berkeley, Berkeley Artificial Intelligence Research (BAIR), CITRIS, the Sutardja Center, and the Fung Institute.

RISC-V, a royalty-free microprocessor architecture first developed at Berkeley, is emerging as a rival to Arm, the most successful microchip architecture in the world.   The first RISC-V chip was built in 2011 as part of the open source Peer Lab Project by CS Prof. and alumnus Krste Asanović (Ph.D. '98, advisor: John Wawrzynek), CS Prof. Emeritus David Patterson, and CS alumni Andrew Waterman (M.S. 11/Ph.D. '16, advisors: David Patterson/Krste Asanović) and Yunsup Lee (M.S. '11/Ph.D. '16, advisor: Krste Asanović).  Asanović, Waterman and Lee went on to found SiFive, "the first fabless semiconductor company to build customized silicon on RISC-V."   Asanović explains that the architecture has gained momentum "not because it's 10% faster. It's because it's a new business model."  Chip designers traditionally have to find a seller to make their microprocessors, but now designers can select RISC-V and "all suppliers compete for your business.  You can add your own extensions without obtaining permission" or paying license fees.

EECS Prof. Trevor Darrell has been appointed chief scientist at Grabango, a provider of checkout-free technology for brick-and-mortar stores.  Darrell is an expert in computer vision, machine learning and perception-based human computer interfaces, and leads the Berkeley Artificial Intelligence Laboratory (BAIR).  He helped develop Convolutional Architecture for Fast Feature Embedding (Caffe), a deep-learning framework used by computer vision researchers around the world.  Grabango announced earlier this year that it had signed four separate agreements with multibillion-dollar retail partners, presiding over a combined 29-million square feet of shopping space.

NTT Research has announced that it has entered into a three-year Industrial Partnership with the UC Berkeley Simons Institute for the Theory of Computing.  The partnership, which will extend from September  2019 through August  2021, will enable NTT Research’s Cryptography and Information Security (CIS) Lab to join all Simons Institute events, invite select Simons program participants and fellows to one-day visits to NTT Research, and hold a dedicated desk in the Calvin Lab.  The Simons Institute brings the world’s top theoretical computer scientists together with the next generation of scholars to explore problems about the nature and limits of computation.

EE Prof. Ming Wu has been named the 2020 recipient of the IEEE Electron Devices Society (EDS) Robert Bosch Micro and Nano Electro Mechanical Systems (MEMS) Award.  The award was established in 2014 "to recognize and honor advances in the invention, design, and/or fabrication of micro- or nano- electromechanical systems and/or devices" with the proviso that individual contributions "be innovative and useful for practical applications."  Wu was selected "For pioneering contributions in MEMS optical switches and optoelectronic tweezers.”

EECS Postdoctoral researcher Pragya Kushwaha, currently working with Prof. Chenming Hu and Prof. Sayeef Salahuddin in the Berkeley Short-channel IGFET Model (BSIM) group, has won a prestigious 2019 IEEE Electron Devices Society (EDS) Early Career Award.  This award is presented annually to an IEEE EDS member who has made early career contributions to the field.  Kushwaha develops compact models for emerging electronic devices, now considered the industry standard.  The models are used by circuit designers to predict device behavior (i.e., current, power, and noise) to simulate their circuits during design before fabrication. This honor was previously won by BSAC Postdoc Chen Yang in 2010.

CS alumnus Feng Zhou (Ph.D. '07, advisor: Eric Brewer) is the subject of a Bloomberg article titled "The U.S.-trained coder is helping NetEase find new life beyond games."  To help the company remain competitive, NetEase Youdao CEO Zhou is creating an all-in-one learning platform to tap the lucrative overlap between education and technology.  Addressing the pressure many Chinese families feel to prepare children for college entrance exams starting as early as Kindergarten, Zhou says courses can be taught through high-speed live-streaming, enabling smooth communication between teacher and student. Artificial intelligence-powered tutors can grade homework and use data to evaluate student test results.  “That’s what we have always been good at,” said Zhou. “Almost every industry in China has been transformed by the internet, but that’s not yet the case for education.”