Tiffany Perumpail wins Teaching Effectiveness Award

EECS undergraduate Tiffany Perumpail has won a Teaching Effectiveness Award (TEA) from the UC Berkeley Graduate Division.  This very competitive award is bestowed annually by the Graduate Council’s Faculty Advisory Committee for GSI Affairs.  Applicants submit essays in which they identify a problem they encountered in teaching, explain their strategy and rationale in devising a solution, and assess the effectiveness of the solution. Perumpail's essay, about her experience TAing CS61A, is titled "Improvement of Academic Intern Experience and Performance in Introductory Computer Science."  

Oasis Labs ICO is raising funds for Ekiden

The Oasis Labs ICO is raising funds for Ekiden, a next generation blockchain built to address the issues of scalability and security in a low cost manner. Ekiden's decoupled architecture addresses the issues of throughput and security by combining the blockchain with an offchain EVM-scaling solution.  The Oasis Labs team, which is led by Prof. Dawn Song (the co-director of the Initiative for Cryptocurrencies and Contracts), and includes post-doctoral researcher Raymond Cheng and graduate student Noah Johnson, brings a unique combination of both theoretical and applied expertise to the table--as well as experience founding successful tech start-ups.  Oasis Labs is rated in the top 5% of ICOs by Crypto Briefing.

PerfFuzz wins ISSTA18 Distinguished Paper Award

"PerfFuzz: Automatically Generating Pathological Inputs," written by graduate students Caroline Lemieux and Rohan Padhye, and Profs. Koushik Sen and Dawn Song, will receive a Distinguished Paper Award from the ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA) 2018 in Amsterdam in July.  PerfFuzz is a method to automatically generate inputs for software programs via feedback-directed mutational fuzzing.  These inputs exercise pathological behavior across program locations, without any domain knowledge.   The authors found that PerfFuzz outperforms prior work by generating inputs that exercise the most-hit program branch 5x to 69x times more, and result in 1.9x to 24.7x longer total execution paths.

Microsoft acquires Semantic Machines

Semantic Machines, an artificial intelligence startup co-founded by Prof. Dan Klein and staffed by a number of EECS alumni, has been acquired by Microsoft to help Cortana hold more natural dialog with users.  The team has built a number of machine learning components which work together for a smarter AI, and move beyond the more basic back-and-forth currently supported by the Google Assistant, Apple’s Siri, and Amazon’s Alexa.

In addition to Klein, the team includes Percy Liang (Ph.D. '11), David Hall (Ph.D. '12), Adam Pauls (Ph.D. '12), David Burkett (Ph.D. '12), Jason Wolfe (Ph.D. '11 adviser: Stuart Russell), Yuchen Zhang (Ph.D. '16), Taylor Berg-Kirkpatrick (B.A. '08/Ph.D. '15), Greg Durrett (Ph.D. '16), Alex Nisnevich (M.S. '14), current grad student Jacob Andreas, Charles Chen (B.A. CS/Math '11), Andrew Nguyen (B.A. CS/Linguistics '12), Chuck Wooters (Ph.D. Speech Recognition '93), and consultant Prof. Michael Jordan.

Luke Strgar thinks that Blockchain can be used to track gun sales in America

Graduating CS senior Luke Strgar thinks he might have a solution for the fraught issue of guns in America: Use blockchain to track gun sales.  Strgar thinks that Blockchain offers the perfect balance between security, anonymity and scale that could please people on all sides of the gun-control debate.  He spent two days in Washington, D.C. this month pitching the idea of a centralized, ultra-secure, online gun-sale database to legislative aides and think-tank analysts.  A database like this could be monitored by everyone and could not be abused by the government.  “The goal here is to find a solution that both parties can agree on,” Strgar said. “I am not interested in developing something for one side of the discussion, that people try to force down the throat of parties coming from the other side. One of the nice things about technology is that you can develop systems that work for people.”

Nick Carlini embeds hidden commands to Alexa and Siri in recordings of music and spoken text

CS graduate student Nicholas Carlini  is featured in a New York Times article titled "Alexa and Siri Can Hear This Hidden Command. You Can’t." He and his advisor, David Wagner, have published a paper showing they can embed audio instructions, undectable by human beings, directly into recordings of music or spoken text. They can secretly activate the artificial intelligence systems on smartphones and smart speakers, making them dial phone numbers or open websites. In the wrong hands, the technology could be used to unlock doors, wire money or buy stuff online — simply with music playing over the radio.  “We want to demonstrate that it’s possible,” he said, “and then hope that other people will say, ‘O.K. this is possible, now let’s try and fix it.’ ”  Carlini was among a group of researchers who showed in 2016 that they could hide commands in white noise played over loudspeakers and through YouTube videos to get smart devices to turn on airplane mode or open a website.

Jacque Garcia graduates a champion

Graduating CS senior Jacque Garcia, the president of Cal Boxing, is the focus of a Berkeley News article titled "Longtime fighter graduates as a champion."  Garcia, who grew up in Compton and is known for her “mental toughness, determination, dedication and positive attitude,” won the 2018 132-pound National Collegiate Boxing Association (NCBA) championship belt, an Outstanding Boxer Award, and a Cal Boxing women's third-place team award.  She was also both a Code2040 Fellow and CircleCI software engineering intern in 2017, and worked at the Hybrid Ecologies Lab in 2016 to help Ph.D. grad student Cesar Torres develop some features of a 2.5D Computer Aided Design (CAD) tool to reduce complexity of digital modeling by using grey-scale height maps.  Garcia credits the student organization Code the Change for her decision to eventually major in Computer Science. “Graduation is going to be very emotional,” says Garcia. “I didn’t start thinking about college until I was in the eighth grade. I didn’t know if I was going to go to college, I didn’t know how I was going to pay for it. It’s going to be a surreal moment. I can’t believe it’s happening.”

HäirIÖ: Human Hair as Interactive Material

CS Prof. Eric Paulos and his graduate students in the Hybrid Ecologies Lab, Sarah Sterman, Molly Nicholas, and Christine Dierk, have created a prototype of a wearable color- and shape-changing braid called HäirIÖ.  The hair extension is built from a custom circuit, an Arduino Nano, an Adafruit Bluetooth board, shape memory alloy, and thermochromic pigments.  The bluetooth chip allows devices such as phones and laptops to communicate with the hair, causing it to change shape and color, as well as respond when the hair is touched. Their paper "Human Hair as Interactive Material," was presented at the ACM International Conference on Tangible, Embedded and Embodied Interaction (TEI) last week. They have posted a how-to guide and instructable videos which include comprehensive hardware, software, and electronics documentation, as well as information about the design process. "Hair is a unique and little-explored material for new wearable technologies," the guide says.  "Its long history of cultural and individual expression make it a fruitful site for novel interactions."

Allan Jabri named 2018 Soros Fellow

CS graduate student Allan Jabri has been named a 2018 Paul & Daisy Soros Fellow.   Soros Fellowships are awarded to outstanding immigrants and children of immigrants from across the globe who are pursuing graduate school in the United States.  Recipients are chosen for their potential to make significant contributions to US society, culture, or their academic fields, and will receive up to $90K in funding over two years.  Jabri was born in Australia to parents from China and Lebanon and was raised in the US.   He received his B.S. at Princeton where his thesis focused on probabilistic methods for egocentric scene understanding, and worked as a research engineer at Facebook AI Research in New York before joining Berkeley AI Research (BAIR).  He  is interested in problems related to self-supervised learning, continual learning, intrinsic motivation, and embodied cognition. His long-term goal is to build learning algorithms that allow machines to autonomously acquire visual and sensorimotor common sense. During his time at Berkeley, he also hopes to mentor students, contribute to open source code projects, and develop a more interdisciplinary perspective on AI.

Stephen Tu wins Google Fellowship

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.