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.

Prof. Dawn Song and graduate student Noah Johnson are taking a new approach to enable organizations to follow tight data security and privacy policies while enabling flexible data analysis, as well as machine learning for analysts.  Working with Uber, they tested their system using a dataset of 8 million queries written by the company’s data analysts. The system is currently being integrated into Uber’s internal data analytics platform.  With help from the Signatures Innovation Fellows program, they are advancing the system to provide the same level of security and flexibility for a broad range of data analysis and machine learning, whether needed in basic and medical research or business analytics.

Prof. Alexandre Bayen and PhD student Pulkit Agrawal developed a computer vision-based system to help memory care centers monitor patient falls and to reduce them where possible.  State regulations require an MRI of the head any time a patient suffers an unwitnessed fall, and about a fourth of all Alzheimer’s-related hospital visits are triggered by a fall. With five million Americans currently living with Alzheimer’s, the task of preventing, tracking and treating fall-related injuries has become daunting and costly, with more than a $5 billion annual cost to medicare--and the number of people with Alzheimer’s is expected to double in the next 15 years.   A system capable of detecting falls by autonomously monitoring patients and sending therapists video clips could improve the monitoring process immensely  “There are no effective drugs yet to treat Alzheimer’s,” Agarwal says. “Until we have them, we have to help patients where they are. Developing computer vision systems to detect falls and fall vulnerability seemed like a good way to improve healthcare for a growing patient population.”

UC Berkeley's Eta Kappa Nu (HKN) Mu Chapter has won the 2016-17 IEEE-HKN Outstanding Chapter Award.  The Berkeley Mu Chapter of HKN, the the national Electrical and Computer Engineering honor society, is among the most active engineering societies on campus and provides many services to the undergraduate student community including course surveys and a course guide, tutoring and review sessions,  industrial infosessions and a career fair, and department tours for prospective students.   The Outstanding Chapter Award is conferred by the Institute of Electrical and Electronics Engineers (IEEE)-HKN Board of Governors and is presented to HKN chapters in recognition of excellence in their chapter administration and programs.  Berkeley HKN, which has won the Outstanding Chapter Award every year since 1998-99, is advised by Prof. Anant Sahai.  The award will be presented at a conference in Monterey in March.

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.