CS Profs. and alumni David Wagner (Ph.D. '00) and Eric Brewer (B.S. '89), and alumni Ian Goldberg (Ph.D. '00) and Randi Thomas (M.S.) have won the 2019 USENIX Test of Time Award for their 1996 paper titled "A Secure Environment for Untrusted Helper Applications."  The paper, which introduced a fundamental and crucial technique for confining untrusted applications in computer systems, and which made a significant contribution to the computer security field, was written by Wagner, Goldberg and Thomas when they were Brewer's graduate students.  “Beyond its strong academic impact — cited by 890 papers," said award committe member Dan Boneh, "the technique is now used to confine web pages in the Chrome browser, and to confine applications running on Android."

A viral real-time AI art application, co-created by three current and former graduate students of CS Prof. Alexei Efros, has won two coveted awards--Best in Show and Audience Choice--at the SIGGRAPH 2019 Real-Time Live Competition.  The interactive application, called GauGAN, was co-created by Ph.D. candidate Taesung Park during a summer internship at NVIDIA, along with alumni and NVIDIA researchers Jun-Yan Zhu (Ph.D. '17,  ACM SIGGRAPH Outstanding Doctoral Disseration winner) and Ting-Chun Wang (Ph.D. '17), as well as NVIDIAs Ming-Yu Liu.  GauGAN is the first semantic image synthesis model that can turn rough sketches into stunning, photorealistic landscape scenes.

CS Prof. Michael Jordan has written a commentary in the Harvard Data Science Review (HDSR) titled "Dr. AI or: How I Learned to Stop Worrying and Love Economics" (a play on the title of the film Dr. Strangelove).  In it, he  argues that instead of trying to put "‘thought’ into the computer, and expecting that ‘thinking computers’ will be able to solve our problems and make our lives better," he explores the prospect of bringing microeconomics "into the blend of computer science and statistics that is currently being called ‘AI.'"

CS graduate student Shruti Agarwal and her thesis advisor Prof. Hany Farid have created a new weapon in the war against "deepfakes," the hyper-realistic AI-generated videos of people appearing to say and do things they never actually said or did.  The new forensic technique, which uses the subtle characteristics of how a person speaks to recognize whether a new video of that individual is real, was presented this week at the Computer Vision and Pattern Recognition conference in Long Beach.  “The basic idea is we can build these soft biometric models of various world leaders, such as 2020 presidential candidates," said Farid, "and then as the videos start to break, for example, we can analyze them and try to determine if we think they are real or not.”

A paper written by recent graduate Elizaveta Tremsina (B.S. '19 CS/Physics/Applied Math) has taken third place in the undergraduate category of the 2019 ACM Student Research Competition (SRC) Grand Finals.  The paper, titled "Your Story Recorded in a Magnet: Micromagnetic Simulations of Spin-Orbit Torque in Multi-layer Structures," was a continuation of the first place poster she presented at the 2018 Richard Tapia Celebration of Diversity in Computing.    "I am extremely thankful to the Berkeley EECS department for the amazing 4.5 years and for the unique chance to participate in cutting-edge research with Dr. Salahuddin's group and also attend the Tapia conference (my first one back in 2016 and last year)," she said. "I hope that more Berkeley undergrads participate in this competition in the future, be it at Tapia or other ACM conferences."  Tremsina was presented with her award at the ACM awards banquet last weekend.

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.

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.

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.

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 .

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.