Umesh Vazirani and Sanjeev Arora elected to the National Academy of Sciences

Prof. and alumnus Umesh Vazirani (Ph.D. '86) and alumnus Sanjeev Arora (Ph.D. '94) have been elected to the National Academy of Sciences (NAS).  Membership is awarded in recognition of distinguished and continuing achievements in original scientific research.  Vazirani is the Roger A. Strauch Professor of EECS and the co-director of the Berkeley Quantum Computation Center (BQIC). His research interests lie primarily in quantum computing.  Arora, whose interests include uses of randomness in complexity theory and algorithms,  efficient algorithms for finding approximate solutions to NP-hard problems (or proving that they don't exist), and cryptography, is now the Charles C. Fitzmorris Prof. of Computer Science at Princeton University.

Alex Bayen wins 2018 IEEE TCCPS Mid-Career Award

Prof. Alexandre Bayen has won the 2018 Institute of Electrical & Electronics Engineers (IEEE) Technical Committee on Cyber-Physical Systems (TC-CPS) Mid-Career Award.  This award recognizes a mid-career researcher from either academia or industry who has demonstrated outstanding contributions to the field of cyber-physical system (CPS) in his/her career development. CPS addresses the close interactions and feedback loop between the cyber components such as sensing systems and the physical components such as varying environment and energy systems.   Bayen is the director of the Institute for Transportation Studies and heads the Mobile Sensing Lab, which focuses on applications of control and optimization to problems involving data collected by mobile sensors, in particular onboard phones and connected wearables.  His research project Mobile Millennium includes a pilot traffic-monitoring system that uses the GPS in cellular phones to gather traffic information, process it, and distribute it back to the phones in real time.

Jitendra Malik wins IJCAI-18 Award for Research Excellence

Prof. Jitendra Malik has won the 2018 Award for Research Excellence from the International Joint Conferences on Artificial Intelligence Organization (IJCAI).  The Research Excellence award is given to a scientist who has carried out a program of research of consistently high quality throughout an entire career yielding several substantial results. The recipients of this honor, including CS Prof. Michael Jordan who won in 2016, are considered among "the most illustrious group of scientists from the field of Artificial Intelligence."  Malik is known for his research in computer vision.  The award will be presented at the 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence (IJCAI-ECAI 2018) in Stockholm, Sweden, in July.

How David Chaum’s eCash Spawned a Cypherpunk Dream

Alumnus David Chaum (Ph.D. CS/Business Administration '82) is the subject of a Bitcoin Magazine article titled "The Genesis Files: How David Chaum’s eCash Spawned a Cypherpunk Dream." Before most people had heard of the internet, and most homes had personal computers, Chaum was concerned with the future of online privacy.  His 1981 paper, “Untraceable Electronic Mail, Return Addresses, and Digital Pseudonyms” laid the groundwork for research into encrypted communication over the internet.   He designed an anonymous payment system for the internet which he outlined in a 1982 paper titled “Blind signatures for untraceable payments.”   The magazine article focuses on the trajectory of Chaum's subsequent creation of a digital money system called eCash and how his work remains relevant today.

A feasible way for devices to send data with light

Researchers, including Prof. Vladimir Stojanović, have developed a method to fabricate silicon chips that can communicate with light and are no more expensive than current chip technology.  Stojanovic initially led the project into a new microchip technology capable of optically transferring data which could solve a severe bottleneck in current devices by speeding data transfer and reducing energy consumption by orders of magnitude.  He and his collaborators, including Milos Popović at Boston University and Rajeev Ram at MIT, recently published a paper in Nature where they present a manufacturing solution by introducing a set of new material layers in the photonic processing portion of a bulk silicon chip. They demonstrate that this change allows optical communication with no impact on electronics.

Dave Patterson's idea was “going to destroy the computing industry”

Prof. David Patterson is interviewed in the podcast Recode Decode for an episode titled "Meet John Hennessy and Dave Patterson, Silicon Valley’s first disruptors."  He and Hennessy won the 2018 Turing Award--the computer science equivalent of the Nobel Prize--in recognition of their development of RISC, a more efficient computer processor found today in billions of devices.   In the episode, hosted by Kara Swisher, they talk about how they overcame resistance from their peers and made RISC a reality.  “This year, there will be 20 billion microprocessors sold,” Patterson said. “And 99 percent of those will be RISC.”

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."

Andrea Goldsmith named ACM Athena Lecturer

2018 EE Distinguished Alumna Andrea Goldsmith (B.A. ’86/M.S. ’91/Ph.D. ’94) has been named the 2018-19 Association for Computing Machinery (ACM) Athena Lecturer for contributions to the theory and practice of adaptive wireless communications, and for the successful transfer of research to commercial technology.  Goldsmith, who is currently the Stephen Harris Professor in the School of Engineering at Stanford,  introduced innovative approaches to the design, analysis and fundamental performance limits of wireless systems and networks. The Athena Lecturer Award, which was initiated by the ACM Council on Women in Computing (ACM-W), celebrates women researchers who have made fundamental contributions to computer science. The award carries a cash prize of $25,000, with financial support provided by Google.

Michael Jordan explains why the AI revolution hasn’t happened yet

In an Op-Ed piece for Medium, CS and Statistics Prof. Michael Jordan examines the limits of AI and argues for the creation of an engineering discipline encompassing data science, intelligent infrastructure (II), and intelligence augmentation (IA).   Principles of analysis and design must be applied when building planetary-scale inference-and-decision-making systems because they will have a profound effect on human lives.   "We need to realize that the current public dialog on AI — which focuses on a narrow subset of industry and a narrow subset of academia — risks blinding us to the challenges and opportunities that are presented by the full scope of AI, IA and II," he writes.

Michael Laskey talks DART in Robohub podcast

EECS graduate student Michael Laskey (advisor: Ken Goldberg) is interviewed by Audrow Nash for a Robohub podcast titled "DART: Noise injection for robust imitation learning."  Laskey works in the AUTOLAB where he develops new algorithms for Deep Learning of robust robot control policies and examines how to reliably apply recent deep learning advances for scalable robotics learning in challenging unstructured environments.  In the podcast, he discusses how DART relates to previous imitation learning methods, how this approach has been used for folding bed sheets, and on the importance of robotics leveraging theory in other disciplines.