Two EECS faculty and one alumnus are the authors with the most number of papers accepted to the upcoming 2019 Thirty-third Conference on Neural Information Processing Systems (NeurIPS), one of the most popular and influential AI conferences in the world.  CS Prof. Sergey Levine took the top spot with 12 papers, alumnus Francis Bach (Ph.D. '05, advisor: Michael Jordan) was the second most prolific contributor with 10 papers, and Prof. Pieter Abbeel placed third with nine.  Only one in five of the 6,743 papers submitted to the conference this year were accepted.  Registration to be one of the 8,000 attendees at  last year's NeurIPS (formerly NIPS) conference sold out in 12 minutes.  A lottery has been implemented for this year's conference, which will take place in December.

CS alumna Sally Floyd (M.S. '87/Ph.D. '89, advisor: Richard Karp), best known as one of the inventors of Random Early Detection (RED), an active queue management scheme widely credited with saving the internet from collapse in the 1990s, has died at age 69.  Floyd graduated from Berkeley with a B.A. in Sociology in 1971 and, after taking a two-year course in electronics at Meritt College, spent the next decade working as a computer systems engineer at BART.  She returned to Berkeley as a graduate student in 1984 and was known as an outstanding advisor to members of the CS Reentry Program, a department project which prepared  "older" women and minorities, who had bachelor's degrees in non-technical fields, for competitive admission to graduate STEM programs.  The creation of the RED algorithm, which was built on work started by Van Jacobson in the 1980s,  founded the field of Active Queue Management (AQM).  Floyd and Jacobson's 1993 paper describing how RED could control congestion on the internet continues to play a vital role in its stability and has been cited in more than 9,100 articles. “That’s truly huge,” said Prof. Vern Paxson, who had been mentored by Floyd as a graduate student, “up there with the most fundamental papers in computer networking.”

Berkeley researchers, including EECS Prof. Ming Wu and his former postdoc Youming Wang,  have created the fastest silicon-based, programmable two-dimensional optical phased array, built on micro-electro-mechanical systems (MEMS).  They achieved a resonance frequency of 55 kilohertz that corresponded to a response time of 5.7 microseconds, almost 1,000 times faster than a traditional optical phased array built on liquid crystal. With a large array of 25,600 pixels packed onto a chip that is 3.1 by 3.2 millimeters, the device can also capture very high-resolution images of its surroundings and lead to cheaper and more efficient medical-imaging devices, optical communications and holographic televisions, as well as more robust LiDAR sensors for self-driving cars.  "Being able to program these chips allows us to go beyond scanning, we can program our arrays to be more like human eyes. This allows us to generate and perceive arbitrary patterns like our eyes do; we can track individual objects instead of just rotating scanning,” said Wu.

Berkeley Remix Podcast Season 4, Episode 2, explores the contributions of UC Berkeley Engineering to the rise of the semiconductor industry in Silicon Valley in the 1960s and 70s.   “Berkeley Lightning: A Public University’s Role in the Rise of Silicon Valley”  focuses on the development of SPICE, the first widely used design program for prototyping microchips, which was originally designed by and for students.  The software spread "like lightning" in part because Berkeley, as a public institution, made it available free of charge. The world has not been the same since.  The podcast features audio from interviews with Prof. Emeritus  Paul Gray  and alumnus Laurence Nagel (B.S. '69/M.S. '70/Ph.D. '75, advisor: Donald Pederson), CEO of Omega Enterprises, and former senior manager at Bell Laboratories.

EECS students, postdocs, alumni, and faculty were front and center at the 28th USENIX Security Symposium in Santa Clara last week.  In addition to the Test of Time and Distinguished Paper Awards (see below), Keynote Speaker Alex Stamos (B.S. '01), previously the Chief Security Officer of Facebook, highlighted the threat model work of current ICSI postdoc Alisa Frik (advisor: Serge Egelman).  Alumnus Nicholas Carlini (Ph.D. '18, advisor: David Wagner) gave a talk on his neural networks research which was co-authored by CS Prof. Dawn Song and postdoc Chang Liu.  ICSI researchers Primal Wijesekera and Serge Egelman, and former ICSI postdoc Joel Reardon, were awarded a Distinguished Paper Award for "50 Ways to Leak Your Data: An Exploration of Apps' Circumvention of the Android Permissions System." Grad students Frank Li (advisor: Vern Paxson) and Nathan Malkin (advisors: Serge Egelman and David Wagner), received a Distinguished Paper award at the SOUPS '19 technical session for "Keepers of the Machines: Examining How System Administrators Manage Software Updates For Multiple Machines." The Zip Bomb research of alumnus David Fifield (Ph.D. '17, advisor: Doug Tygar) was also awarded a Best Paper award at the WOOT '19 technical session.

Two CS grad students, co-advised by David Culler and Raluca Popa, also made presentations.  Sam Kumar presented "JEDI: Many-to-Many End-to-End Encryption and Key Delegation for IoT" and Michael P. Andersen presented "WAVE: A Decentralized Authorization Framework with Transitive Delegation."

Graduate student Grant Ho and his co-advisors Profs. Vern Paxson and David Wagner, were honored with a Distinguished Paper Award at the 2019 USENIX Security Symposium for "Detecting and Characterizing Lateral Phishing at Scale".  In the paper, they presented "the first large-scale characterization of lateral phishing attacks, based on a dataset of 113 million employee-sent emails from 92 enterprise organizations."  Ho, Paxson, and Wagner previously won the same award at the 2017 USENIX Security Symposium for their paper "Detecting Credential Spearphishing Attacks in Enterprise Settings."

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 group of researchers currently or formerly working in the lab of CS Affiliate Prof. Jack Gallant, have developed interactive semantic maps that can predict where different categories of words activate the brain. The researchers used functional MRI to scan the brains of subjects who were listening to or reading stories.  The results were viewed in an interactive, 3D, color-coded map, where words are presented as scribbles of color on a flattened brain cortex.  When the researchers compared the listening-versus-reading brain activity data, they found the maps they created from both datasets were virtually identical. The maps may one day inform interventions for dyslexia, strokes, epilepsy, brain injuries, and auditory processing disorders.

A paper co-authored by EE Prof. Ali Javey, describes a new sweat sensor design that can be rapidly manufactured using a “roll-to-roll” processing technique that essentially prints the sensors onto a sheet of plastic like words on a newspaper.  The sensors monitor sweat rate and the electrolytes and metabolites in sweat.  “The goal of the project is not just to make the sensors but start to do many subject studies and see what sweat tells us — I always say ‘decoding’ sweat composition,” said Javey.  “For that we need sensors that are reliable, reproducible, and that we can fabricate to scale so that we can put multiple sensors in different spots of the body and put them on many subjects."