News

Berkeley paper wins 2018 IEEE EDS George E. Smith Award

"Improved Subthreshold Swing and Short Channel Effect in FDSOI n-Channel Negative Capacitance Field Effect Transistors," has won the 2018 IEEE Electron Devices Society (EDS) George E. Smith Award.  The paper was co-authored by current postdoc Korok Chatterjee, graduate student Ava J. Tan, former postdocs Daewoong Kwon,  Angada B. Sachid, Ajay K. Yadav and Hong Zhou, EE Profs. Chenming Hu and Sayeef Salahuddin, and LBNL's Roberto dos Reis. The award recognizes the best paper appearing in a fast turn around archival publication of the IEEE Electron Devices Society, targeted to IEEE Electron Device Letters.

Justin Yim wins Best Student Paper Award at ICRA 2019

EECS PhD student Justin Yim (with advisor EECS Prof. Ron Fearing and ME undergraduate co-author Eric Wang) has won the best student paper award at the 2019 IEEE International Conference on Robotics and Automation (ICRA) (May 20-24, Montreal) for his paper "Drift-free Roll and Pitch Estimation for High-acceleration Hopping."  The robot "Salto" (Saltatorial Agile Locomotion on Terrain Obstacles) was previously restricted to only indoor operation in a room equipped with a motion tracking system. In the newest paper, Salto can now estimate its own position by combining its onboard inertial sensor with a model of its takeoffs and landings. This improved estimate allows
Salto to hop outside with human steering.

Tianshi Wang and Jaijeet Roychowdhury win UCNC 2019 Best Paper Award

A paper co-authored by freshly minted alumnus Tianshi Wang (Ph.D. '19, winner of the 2019 EECS David Sakrison Memorial Prize for "truly outstanding research") and Prof. Jaijeet Roychowdhury has won Best Paper Award at the International Conference on Unconventional Computation and Natural Computation (UCNC) 2019.  The paper, titled "OIM: Oscillator-based Ising Machines for Solving Combinatorial Optimisation Problems" will be presented at the conference in Japan next week.

With a hop, a skip and a jump, Salto leaps over obstacles with ease

Salto the robot, first unveiled in 2016 by the Biomimetic Millisystems Lab, is now equipped with a slew of new skills, giving it the ability to bounce in place like a pogo stick and jump through obstacle courses like an agility dog. Salto can even take short jaunts around campus, powered by a radio controller.  Salto creators Justin Yum, Eric Wang and Ronald S. Fearing will describe the robot’s new skills today (Tuesday, May 21) at the 2019 International Conference on Robotics and Automation in Montreal.

Chelsea Finn wins 2018 ACM Doctoral Dissertation Award

Recent graduate Chelsea Finn (Ph.D. '18, advisors: Pieter Abbeel and Sergey Levine), has won the prestigious ACM Doctoral Dissertation Award. This award is presented annually to "the author(s) of the best doctoral dissertation(s) in computer science and engineering."  In her dissertation, "Learning to Learn with Gradients," Finn introduced algorithms for meta-learning that enable deep networks to solve new tasks from small datasets, and demonstrated how her algorithms can be applied in areas including computer vision, reinforcement learning and robotics.  Finn  is currently a research scientist at Google Brain, a post-doc at the Berkeley AI Research Lab (BAIR), and an acting assistant professor at Stanford.  Last year's recipient, Aviad Rubinstein, was also a Berkeley EECS alum.

Soham Phade and Venkat Anantharam win GameNets Best Paper Award

Graduate student Soham Phade and his advisor, Venkat Anantharam, have won the Best Paper Award at the 9th EAI International Conference on Game Theory for Networks (GameNets 2019).  Their paper, titled "Optimal Resource Allocation over Networks via Lottery-Based Mechanisms," was in the Games for Economy and Resource Allocation category.  Phade's current focus is on "designing market-based mechanisms and algorithms on presumably more accurate models of human behavior from psychology and decision theory, for increasing human welfare and for building more efficient commercial systems that interact with humans."

Two papers selected as 2018 IEEE Micro Top Picks

Two papers by EECS faculty have been named 2018 IEEE Micro Top Picks by the Association for Computing Machinery (ACM) Special Interest Group on Computer Architecture (SIGARCH).  The papers were "A Hardware Accelerator for Tracing Garbage Collection," co-authored by Profs. Krste Asanović and John Kubiatowicz (along with Martin Maas), and "FireSim: FPGA-Accelerated Cycle-Exact Scale-Out System Simulation in the Public Cloud," co-authored by Profs. Borivoje Nikolić, Randy Katz, Jonathan Bachrach, and Krste Asanović (along with Karandikar, Mao, Kim, Biancolin, Amid, Lee, Pemberton, Amaro, Schmidt, Chopra, Huang and Kovacs).  Top Picks represent "the most significant research papers in computer architecture based on novelty and potential for long-term impact."  The papers will be published in IEEE Micro's annual “Top Picks from the Computer Architecture Conferences” issue in May/June 2019.

Negative capacitance found

A research paper by EECS Prof. Sayeef Salahuddin's group that shows direct measurement of Negative Capacitance was highlighted in an article in Nature Electronics titled "Negative capacitance found."   Negative Capacitance is a new state of ferroelectric material that was discovered by Salahuddin in 2008 and promises to significantly improve energy efficiency in electronics.

Dan Garcia

Dan Garcia tops list of most frequent SIGCSE submissions

CS Teaching Prof. and alumnus Dan Garcia (M.S. '95/Ph.D. '00) has authored more submissions in the 50 year history of the Association for Computing Machinery (ACM) Special Interest Group on Computer Science Education (SIGCSE) than anyone else.  Garcia authored 61 SIGCSE submissions accepted between 2003 and 2016 (submissions were counted from 1969 to 2018).  This count is particularly impressive since he was precluded from submitting papers in 2017 and 2018 because he was serving as program co-chair and symposium co-chair, respectively.  It also  doesn't include his 5 accepted submissions in 2019.   Berkeley ranked #3 for the highest number of accepted papers (114) and #9 for the most citations (302) in SIGCSE's history .

Nine papers make four Top 10 lists in TOPBOTS AI research rankings

9 papers co-authored by 6 EECS faculty, 13 students,  3 post docs, and 3 alumni have made it into the Top 10 research papers ranked by TOPBOTS in four categories of AI Research. TOPBOTS is the largest publication, community, and educational resource for business leaders applying AI to their enterprises.  3 papers co-authored by Sergey Levine made the #1, #3, and #9 spots in "What Are Major Reinforcement Learning Achievements & Papers From 2018?"  A paper co-authored by Moritz Hardt ranked #5 in "Top 2018 AI research papers" and #3 in  "Recent Breakthrough Research Papers In AI Ethics." A paper co-authored by Jitendra Malik ranked #7 in the Top 2018 papers and #5 in "10 Cutting Edge Research Papers In Computer Vision & Image Generation."  The #2 Top 2018 paper was co-authored by David Wagner, and a paper co-authored by Alexei Efros ranked #9 in the Computer Vision category.