News

RISC-V grows globally as an alternative to Arm

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.

Robot BLUE named one of 100 greatest innovations of 2019

An affordable, human-friendly robot developed by EECS Prof. Pieter Abbeel and Project Blue is among Popular Science’s “Best of What’s New” innovations for 2019.  BLUE (Berkeley robot for Learning in Unstructured Environments) uses artificial intelligence and deep reinforcement learning algorithms to adapt to and operate safely in unpredictable settings, including the common household.  The list is  Popular Science's ranking of the year’s top 100 technologies and products, which highlight feats of engineering, breakthrough software and other acclaim-worthy discoveries from the past year.  BLUE is projected to ship to consumers in the next few years,

Dawn Song named 2019 ACM Fellow

EECS Prof. and alumna Dawn Song (Ph.D. '02, advisor: Doug Tygar) has been  selected as a 2019 Fellow of the Association for Computing Machinery (ACM).    Song was cited "For contributions to security and privacy" and is now part of an elite group that represents less than 1% of the Association’s global membership.  As one of the world’s foremost experts in computer security and trustworthy artificial intelligence, Song founded a startup to build a new platform based on a paradigm in which people control their data and are compensated for its use by corporations. She was named to both the 2019 WIRED25 list of innovators and Inc.com's list of the 100 most innovative businesswomen in 2019.   Fellows will be honored at an awards banquet in June.

Trevor Darrell joins checkout-free company Grabango

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.

Prof. Chenming Hu

Chenming Hu wins 2020 IEEE Medal of Honor

EECS Prof. Chenming Hu has been awarded the 2020 IEEE Medal of Honor, the highest honor awarded by the Institute of Electrical and Electronics Engineers (IEEE).  The medal is presented when "a candidate is identified as having made a particular contribution that forms a clearly exceptional addition to the science and technology of concern to IEEE."  Hu, whose seminal work on metal-oxide semiconductor MOS reliability and device modeling has had enormous impact on the continued scaling of electronic devices, was cited for “For a distinguished career of developing and putting into practice semiconductor models, particularly 3-D device structures, that have helped keep Moore’s Law going over many decades.”  He won the National Medal of Technology and Innovation in 2016 and was named to the Silicon Valley Engineering Hall of Fame in 2017.

Michael Jordan wins 2020 IEEE John von Neumann Medal

CS Prof. Michael I. Jordan has won the prestigious John von Neumann Medal from the Institute of Electrical and Electronics Engineers (IEEE).  The award was established in 1990 to acknowledge "outstanding achievements in computer-related science and technology."    Jordan, who was ranked as the world's most influential computer scientist in 2016 by Science magazine, was cited for "For contributions to machine learning and data science."  Jordan began developing recurrent neural networks as a cognitive model in the 1980s, was prominent in the formalisation of variational methods for approximate inference, and popularised both the expectation-maximization algorithm and Bayesian networks among the machine learning community.  Jordan is the fifth Berkeley CS faculty member to win this award.

Katherine Yelick wins Outstanding Leadership in HPC Award

EECS Prof. Katherine Yelick was honored with an HPCwire Editor’s Choice Award for Outstanding Leadership in HPC at the 2019 International Conference for High Performance Computing, Networking, Storage and Analysis (SC19).  Yelick, who serves as the Associate Laboratory Director for Computing Sciences at Lawrence Berkeley National Laboratory (Berkeley Lab) and who was the director of the National Energy Research Scientific Computing Center (NERSC)  from 2008 to 2012,  is widely recognized for her leadership in research to improve the programmability of high performance computing (HPC) through innovations to programming languages and runtime systems.  Her contributions to design and compiler research were key to the success of patrician global address space (PGAS) for expressing applications with irregular communication patterns on parallel machines, and she is well known for co-inventing the Unified Parallel-C and Titanium languages.

CS cohort to lead Data Systems revolution at Berkeley

Recently hired Prof. Jelani Nelson and Assistant Profs. Raluca Ada Popa, Joseph Gonzalez,  Alvin Cheung, Aditya Parameswaran, and Natacha Crooks, have joined veteran Profs. Joseph Hellerstein and Ion Stoica to form a new cohort of faculty at Berkeley who will conduct academic research into systems to analyze and manage data.   The group, which also includes IEOR Assistant Prof. Barna Saha, will focus on diverse facets of data systems, from protecting data security, to developing systems for massively-scalable machine learning, to working with data distributed across the globe.  “Data systems have become the foundation not only of computer science, but of modern society.  And they are changing fast,” said Hellerstein. “This amazing new cohort is evidence of Berkeley’s commitment to drive diverse innovation and train the next generation of data systems engineers.”

Two EECS papers win 2019 ACM SIGPLAN Distinguished Paper Awards

Two papers co-authored by Berkeley EECS authors won ACM SIGPLAN Distinguished Paper Awards at the Conference on Object-Oriented Programming, Systems, Languages, and Applications (OOPSLA) 2019.  "Duet: An Expressive Higher-Order Language and Linear Type System for Statically Enforcing Differential Privacy" co-authored by Prof. Dawn Song (Ph.D. '02, advisor: Doug Tygar), graduate student Lun Wang, undergraduate researcher Pranav Gaddamadugu, and alumni Neel Somani (CS B.A.  '19), Nikhil Sharma (EECS B.S. '18/M.S. '19),  and Alex Shan (CS B.A. '18), along with researchers in Vermont and Utah, and "Aroma: Code Recommendation via Structural Code Search" co-authored by Prof. Koushik Sen (along with authors at Facebook and UC Irvine), won two of the five honors awarded at the top programming language conference, part of the ACG SIGPLAN conference on Systems, Programming, Languages, and Applications: Software for Humanity (SPLASH) in October.  

Dawn Song is building a world where data privacy exists online

CS alumna and Prof. Down Song (Ph.D. '02, advisor: Doug Tygar) is the subject of a New York Times article titled "Building a World Where Data Privacy Exists Online."  One of the world’s foremost experts in computer security and trustworthy artificial intelligence, Song founded a startup called Oasis Labs to build a new platform based a paradigm in which people control their data and are compensated for its use by corporations.  She and her colleagues believe that by marrying specialized computer chips and blockchain technology, they can build a system that provides greater scalability and privacy protection.  This year, Song made the Wired25  list top 25 innovators as well as Inc.'s second annual Female Founders 100 list as a "Money Mover."