EECS Prof. Stuart Russell has penned a New York Times Op-Ed titled "How to Stop Superhuman A.I. Before It Stops Us," in which he explains why we need to design artificial intelligence that is beneficial, not just smart.  "Instead of building machines that exist to achieve their objectives," he writes, we need to build "machines that have our objectives as their only guiding principle..."   This will make them "necessarily uncertain about what these objectives are, because they are in us — all eight billion of us, in all our glorious variety, and in generations yet unborn — not in the machines."  Russell has just published a book titled "Human Compatible: Artificial Intelligence and the Problem of Control" (Viking , October 8, 2019).

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.

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.

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 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.

Research co-authored by grad student Justin Yim and EE Profs. Ron Fearing and Robert Full, among others, has resulted in the creation of a small cockroach-inspired robot so hardy that it can survive being crushed underfoot.  The robot, which is about the size of a large postage stamp, is made of a thin sheet of a piezoelectric material called polyvinylidene fluoride (PVDF).  Applying electric voltage to PVDF causes it to expand or contract, creating oscillations that propel the device forward.  The robot can sail along the ground at a speed of 20 body lengths per second, said to be the fastest pace among insect-scale robots.  Their paper was published in the journal Science Robotics.

Prof. Eli Yablonovitch is the co-author of a paper published in the Proceedings of the National Academy of Sciences (PNAS) that describes a groundbreaking discovery which has allowed researchers to raise the efficiency of thermophotovoltaics from 23% (where it has stayed for 15 years) to an unprecedented 29%. This ultralight alternative power source could allow drones and other unmanned aerial vehicles to operate continuously for days.  The paper, "Ultraefficient thermophotovoltaic power conversion by band-edge spectral filtering," co-authored by a 10-person research team that includes postdoc Luis Pazos-Outon, details how a highly reflective mirror installed on the back of a photovoltaic cell can reflect low energy infrared photons to reheat the thermal source, providing a second chance for a high-energy photon to be created and generate electricity.

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.'"