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.

Jaijeet Roychowdhury and Tianshi Wang win 2019 Nokia Bell Labs Prize

EECS Prof. Jaijeet Roychowdhury and his graduate student Tianshi Wang have won First Place in the 2019 Nokia Bell Labs Competition for their work on  “A Classical Spin on Quantum Computing.”  The pair have created a new type of processor element that will be significantly more efficient in computing the answers to discrete optimization problems. Their innovation will complement conventional digital processors (CPUs and GPUs) by efficiently tackling a wide range of computationally hard problems of importance in in many diverse areas, including 5G communication systems; complex tasks in planning, scheduling and control; and even the discovery of new drugs.  The first place finish comes with a prize of $100K.

Student research projects to be highlighted at Data Science Showcase

The Data Science Showcase, which will highlight the amazing ways that students are using data science to advance discovery and impact across campus and beyond in over 30+ projects, will be held this Thursday, December 5, from 12 noon to 3:30 pm in Sutardja Dai Hall.  The Showcase will kick off with a series of presentations in the Banatao Auditorium, followed by posters, demonstrations, and light refreshments in the adjoining Kvamme Atrium.  RSVP requested.

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.

NTT Research partners with the Simons Institute

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.

Ashwin Pananjady wins inaugual IMS Lawrence Brown PhD Student Award

EECS graduate student Ashwin Pananjady (advisors: Martin Wainwright and Thomas Courtade) is one of the three inaugural recipients of the Institute of Mathematical Statistics (IMS) Lawrence D. Brown PhD Student Award.  Pananjady, who studies fundamental problems spanning statistics, information theory, optimization, and machine learning, will present his research at a special invited session during the 10th World Congress in Probability and Statistics (WC2020), to be held in Seoul, Korea, next year.