A team of researchers led by EE Prof. Sayeef Salahuddin and his graduate student, Suraj Cheema, have managed to grow an ultra-thin material on silicon that can power tiny electronic devices at the atomic scale.  Prior to this fundamental breakthrough, the thinnest conventional material that could demonstrate stable ferroelectricity was 3 nanometers thick.  The new ultrathin material, made of doped hafnium oxide just 1 nanometer thick (equivalent to the size of two atomic building blocks), can demonstrate even stronger ferroelectricity than material several times thicker.  This means it can efficiently power increasingly smaller devices, including memory and logic chips, batteries and sensors, with lower amounts of energy.  The findings were published in the April 22 issue of Nature.

EECS Prof. and alumnus Chenming Hu (M.S. '70/Ph.D. '73) is the subject of an IEEE Spectrum article titled "The father of FinFets: Chenming Hu took transistors into the third dimension to save Moore's Law" (Volume: 57 , Issue: 5 , May 2020).    Hu devised a way around a limitation in semiconductor design that threatened to keep transistors from getting smaller by innovating a technology called FinFET (Fin Field-Effect Transistors) in the IEEE Spectrum.  His idea was to raise  the channel through which current flows so that it sticks out above the surface of the chip like the fin of a shark.   Hu, who extended manufacturers' ability to miniaturize chips beyond what was expected by decades, won the National Medal of Technology and Innovation in 2016 and the IEEE Medal of Honor in 2020.   The article charts Hu's winding career path, the nature of his research and the impact of his contributions.

EE Prof. and alumnus Chenming Hu (M.S. '70, Ph.D. '73), who won the 2020 IEEE Medal of Honor, has chosen to donate his $50K prize to the EECS department.   Hu, who was cited “for a distinguished career of developing and putting into practice semiconductor models, particularly 3D device structures, that have helped keep Moore’s Law going over many decades," is also the subject of an IEEE Spectrum article.  He was hired on the Berkeley faculty in 1976 and has been called the "Father of the 3D Transistor" due to his development of the Fin Field Effect Transistor in 1999.  Intel, the first company to implement FinFETs in its products, called the invention the most radical shift in semiconductor technology in more than 50 years.

The Accel Scholars program, a joint venture between Silicon Valley venture capital firm Accel and the EECS Department, was created to empower undergraduate engineering and computer science students by providing access to Silicon Valley leadership, personalized mentorship, and an industry-relevant curriculum that covers topics not generally taught in class— like how to grow a career, how to build a professional network, and how to raise money to start a company.  Accel Scholars is open to all Berkeley undergraduates who have demonstrated leadership, excellence in their pursuits, and/or a deep passion for a particular area of their discipline.  Apply by visiting the Accel Scholars page on the EECS website until April 5, 2020.

CS Assistant Prof. Alvin Cheung has won a VMware Early Career Faculty Award.  The award recognizes recently appointed faculty "whose research interests and accomplishments seem poised to have significant impact within the industry and academia."  Cheung's research interests include program analysis, program synthesis, improving database application performance, and building large-scale data systems in general. The award comes with a $50K grant and opportunities to collaborate with VMware.

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.