EE graduate student Stephen Tu (advisor: Ben Recht) has been awarded a 2018 Google Fellowship.  Google Fellowships are presented to exemplary PhD students in computer science and related areas to acknowledge contributions to their chosen fields and provide funding for their education and research. Tu's current research interests "lie somewhere in the intersection of machine learning and optimization" although he previously worked on multicore databases and encrypted query processing.  Tu graduated with a CS B.A./ME B.S. from Berkeley in 2011 before earning an EECS S.M. from MIT in 2014.

Graduate student Xue Bin “Jason” Peng (advisors Pieter Abbeel and Sergey Levine) has made a major advance in realistic computer animation using deep reinforcement learning to recreate natural motions, even for acrobatic feats like break dancing and martial arts. The simulated characters can also respond naturally to changes in the environment, such as recovering from tripping or being pelted by projectiles.  “We developed more capable agents that behave in a natural manner,” Peng said. “If you compare our results to motion-capture recorded from humans, we are getting to the point where it is pretty difficult to distinguish the two, to tell what is simulation and what is real. We’re moving toward a virtual stuntman.”  Peng will present his paper at the 2018 SIGGRAPH conference in August.

Undergraduate students Ganeshkumar Ashokavardhanan (EECS  + Business M.E.T.),  Naomi Jung (CS BA), and Louie McConnell (EECS + Business M.E.T.) have been selected to participate in the 2018 KPCB Engineering Fellows Program, named one of the top 5 internship programs by Vault.  Over the course of a summer, KPCB Engineering Fellows join portfolio companies, where they develop their technical skills and are each mentored by an executive within the company. It offers students an opportunity to gain significant work experience at Silicon Valley startups, collaborating on unique and challenging technical problems.

A paper released on arXiv last week by a team of researchers including Prof. Dawn Song and Ph.D. student Nicholas Carlini (B.A. CS/Math '13), reveals just how vulnerable deep learning is to information leakage.  The researchers labelled the problem “unintended memorization” and explained it happens if miscreants can access to the model’s code and apply a variety of search algorithms. That's not an unrealistic scenario considering the code for many models are available online, and it means that text messages, location histories, emails or medical data can be leaked.  The team doesn't “really know why neural networks memorize these secrets right now, ” Carlini says.  “At least in part, it is a direct response to the fact that we train neural networks by repeatedly showing them the same training inputs over and over and asking them to remember these facts."   The best way to avoid all problems is to never feed secrets as training data. But if it’s unavoidable then developers will have to apply differentially private learning mechanisms, to bolster security, Carlini concluded.

CS graduate student Ling-Qi Yan (advisors: Ravi Ramamoorthi/Ren Ng) and researchers at U.C. San Diego are the subject of an article in TechXplore titled "Scientists improve computer rendering of animal fur."  He is part of a team that developed a method for dramatically improving the way computers simulate fur, and more specifically, the way light bounces within an animal's pelt.  The researchers are using a neural network to apply the properties of a concept called subsurface scattering to quickly approximate how light bounces around fur fibers.  The neural network only needs to be trained with one scene before it can apply subsurface scattering to all the different scenes with which it is presented. This results in simulations running 10 times faster than current state of the art.  "We are converting the properties of subsurface scattering to fur fibers," said Yan. "There is no explicit physical or mathematical way to make this conversion. So we needed to use a neural network to connect these two different worlds."  The researchers recently presented their findings at the SIGGRAPH Asia conference in Thailand.

For the second year running, UC Berkeley has won the Fiesta Bowl Overwatch Collegiate National Championship, sweeping UC Irvine 3-0.  CS majors Kevin "SlurpeeThief" Royston and Gandira “Syeikh” Prahandika were on the Berkeley team, which battled in front of a sold-out crowd at the game in Tempe, Arizona, the first partnership between a collegiate bowl game and eSports tournament.  Royston, who was profiled in on Overwatch Wire article before the tournament, is in the top 1% of all players worldwide, has had a peak skill rating of 4626, and was on the winning team last year.  He notes that the balance between esports and school has been a tough road.  “It’s definitely rough, this week is the first time I had a homework assignment slip because of Overwatch. (Laughs) Hear me out! It’s for Machine Learning which is the hardest class at Berkeley. We had to travel (for the Fiesta Bowl) and I worked sixteen hours on an assignment and didn’t even get halfway through it.”  Overwatch is a team-based shooter game that was created by Blizzard Entertainment and released in 2016.  Teams are made up of six players, who select different characters, known in the game as “heroes,” to complete different objectives. The Berkeley team won $42,000 of the $100,000 total in scholarships and other prizes.

The  Cal Alumni Association and the Black Alumni Club are hosting an event Celebrating Diversity in Engineering and Science at Cal on February 10, 2018.  It will honor the 50th anniversary of the Black Engineering and Science Student Association (BESSA) and the 30th anniversary of the Black Graduate Engineering and Science Students (BGESS) group at Berkeley, and will feature both alumni and current students.  The keynote speaker is EECS alumnus Gary S. May (M.S. '88 and Ph.D. '92), now the Chancellor of the University of California, Davis.  In addition to the evening event, BESSA and BGESS alumni are planning an afternoon symposium with panels of engineering alumni to discuss their careers in industry and academia with undergrad, graduate and high school students

Profs. Dawn Song, Ion Stoica, Kurt Keutzer, Michael Jordan, Pieter Abbeel, and Trevor Darrell have teamed up with EECS alumnus Cameron Baradar (B.S. '15) and startup institute The House to run a new "global center-of-gravity of AI activity" called AI@The House. The new program will offer technical guidance, mentorship, free graphic processing units and financial support, among other resources, to startups focused on AI.  Their first core initiative is an accelerator for startups who are leveraging AI to build industry-defining products.

A new initiative, Graduates for Engaged and Extended Scholarship around Computing & Engineering (GEESE), aims to address growing concerns about the rapid advancement and integration of technologies in the global arena by building a coalition of engineers and social science scholars across campus to engage in issues vital to society and technology.  GEESE, launched this semester as one of CITRIS's Tech for Good initiatives,  plans to build a campus community of grad students and postdocs who will bring together disciplines and perspectives from fields like law, public policy, economics, anthropology, sociology, and philosophy, to promote cross-disciplinary scholarship on issues that cannot be wholly addressed from the silos of individual fields.  They will hold roundtables on relevant issues to gauge students' interests, and organize seminars with thought leaders to reflect and redefine their mission and acitivities.

All four EECS students nominated for this year's Computing Research Association (CRA) Undergraduate Researcher Award were recognized by the selection committee.  Senior CS/Math major Garrett Thomas (nominated by Pieter Abbeel) and EECS junior Peter Manohar (nominated by Alessandro Chiesa) were named as finalists.  Senior CS major Siqi Liu (nominated by Sanjam Garg) and CS/Statistics/Math senior Tianhe Yu (nominated by Sergey Levine and Pieter Abbeel) merited honorable mentions.  This award program recognizes undergraduate students in North American universities who show outstanding research potential in an area of computing research.