Ming Wu awarded 2017 C.E.K. Mees Medal from the Optical Society of America

Prof. Ming Wu has been awarded the 2017 C.E.K. Mees Medal from the Optical Society of America (OSA). This medal is presented to a recipient who exemplifies the thought that "optics transcends all boundaries." This award recognizes an original use of optics across different fields. Prof. Wu is being recognized for the invention of “optoelectronic tweezers” that enable massively parallel manipulation of individual biological cells controlled by digital optical projectors.

Jitendra Malik will be a keynote speaker at the 2017 Embedded Vision Summit

EECS Chair and CS Prof. Jitendra Malik will discuss Deep Visual Understanding from Deep Learning as one of the keynote speakers at the Embedded Vision Summit on May 2, 2017.  The summit is the only event focused exclusively on the technologies, hardware, and software that bring visual intelligence to products.  This year, "It's all about deployable computer vision and deep learning" and will feature more than 90 expert presenters in 4 conference tracks over three days.

Kathy Yelick elected to the American Academy of Arts and Sciences

Prof. Katherine Yelick has been elected to the American Academy of Arts and Sciences. This organization has been serving the nation as a champion of scholarship, civil dialogue and useful knowledge since 1780. The Academy convenes leaders from the academic, business, and government sectors to address critical challenges facing our global society. Kathy joins a long list of distinguished members, going back to Ben Franklin, Alexander Graham Bell, and most recently our own Scott Shenker in 2016. For a complete list of EECS members elected to the academy, see EECS Faculty Awards/American Academy of Arts and Sciences.

Google TPUs are built for inference

CS Prof. Emeritus David Patterson co-authored and presented a report on Tensor Processing Units (TPUs) at a regional seminar of the National Academy of Engineering, held at the Computer History Museum in Menlo Park on April 5, 2017.   TPUs, which have been deployed in Google datacenters since 2015, are printed-circuit cards which are inserted into existing servers and act as co-processors tailored for neural-network calculations.  Prof. Patterson says that TPUs are "an order of magnitude faster than contemporary CPUs and GPUs" with an even larger relative performance per watt.  According to an article for the IEEE Spectrum, TPUs are "built for doing inference," having hardware that operates on 8-bit integers rather than the higher-precision floating-point numbers used in CPUs and GPUs.

Beauty and Joy of Computing curriculum receives grant from InfoSys

The Beauty and Joy of Computing, an introductory computer science curriculum taught by Prof. Dan Garcia has received a $311,975 grant from InfoSys for a Professional Development week “BJCpalooza” for teachers to be held July 17-21, 2017 at UC Berkeley. Approximately 200 high school teachers from across the United States will be attending. Prof. Garcia will also be giving the keynote talk at the 2017 ACM TURC (SIGCSE) China, a new leading international forum at the intersection of computer science and the learning sciences, seeking to improve practice and theories of CS education.

Meet Ray, the Real-Time Machine-Learning Replacement for Spark

CS Prof. Michael Jordan, graduate students Philipp Moritz and Robert Nishihara, and research in the RISELab are featured in a Datanami article titled "Meet Ray, the Real-Time Machine-Learning Replacement for Spark."  Ray is one of the first technologies to emerge from RISELab, the successor to AMPLab and its host of influential distributed technologies including Spark, Mesos, and Tachyon. Ray is a new distributed framework designed to enable Python-based machine learning and deep learning workloads to execute in real-time with MPI-like power and granularity. This framework is ostensibly a replacement for Spark, which is seen as too slow for some real-world AI applications.

The Beauty & Joy of Computing featured in the New York Times

Dr. Daniel Garcia and his course "CS10: The Beauty and Joy of Computing" (BJC) are featured in a New York Times article about curricula designed to develop computational thinking in students.  The article, titled "Learning to Think Like a Computer," covers strategies at a number of top institutions and highlights BJC, a CS course for nonmajors which focuses on the abstract principles underpinning computing instead of just teaching students to code.  “The idea of abstraction,” Dan says, “is to hide the details.”  Concealing layers of information makes it possible to get at the intersections of things, improving aspects of a complicated system without understanding and grappling with each part.  The abstraction of computational thinking allows advances without having to redesign from scratch and offers a new language and orientation to tackle problems in many other areas of life.

Paper authored by EECS alumni receives 2017 NSDI Test-of-Time Award.

The paper “X-Trace: A Pervasive Network Tracing Framework”, authored by EECS alumi Rodrigo Fonseca (Ph.D. ’08) and George Porter (Ph.D. ’08) and Professors Randy Katz, Scott Shenker, and Ion Stoica, has received the 2017 Networked Systems Design and Implementation (NSDI) Test-of-Time Award. X-Trace was not the first tracing framework, but it was influential given that it was effectively the first framework for end-to-end tracing to focus on generality and pervasiveness. The researchers implemented X-Trace in protocols and software systems, and in their prize-winning paper, they set out to explain three different use scenarios: domain name system (DNS) resolution; a three-tiered photo-hosting website; and a service accessed through an overlay network.

Tsu-Jae King Liu talks chip efficiency on Moore's Law Panel

EE Prof. Tsu-Jae King Liu, who participated in a semiconductor "Moore's Law" panel discussion at the South by Southwest festival in Texas, is featured in an Electronic Design article  titled "Forget Scaling. Moore's Law Panel Talks Power Consumption."  Tsu-Jae, who helped pioneer the Finfet transistor in 1998, describes some of the ways that transistors and integrated circuits will be evolving and how they might be used in future innovations.

Matthias Vallentin and Vern Paxson take a “VAST” Step Forward in Cyber Security

Postdoctoral researcher Matthias Vallentin is developing VAST,  a  forensic analysis tool  designed to help prioritize the investigation of computer security breaches.  It complements Bro, a security tool  devised by Prof. Vern Paxson when he was a graduate student 22 years ago and which is now used worldwide, to instantly collect huge volumes of log data that a hack might compromise.  “Maybe the external machine also appeared in a phishing email, which contained a PDF attachment. Not only that, but the PDF also includes a malicious payload, which upon opening, sends sensitive information from the employee’s computer to a cyber criminal.  VAST supports this iterative process to reconstruct the complete picture and presents it on a platter” explains Vallentin.  The function, development, and industrial potential of these tools are discussed in a Berkeley Research article.