News

Ash Bhat and Rohan Phadte (James Tensuan)

Rohan Phadte and Ash Bhat are doing what Twitter won't

EECS undergraduate Rohan Phadte and Interdisciplinary Studies major Ash Bhat are the subjects of a Wired article titled "The College Kids Doing What Twitter Won't," about their creation of a Google Chrome browser extension that checks whether Twitter profiles are bots.  It describes the genesis of their partnership, which they call RoBhat Labs, and their efforts to stop the proliferation of fake Twitter accounts from flooding the internet with propaganda. It also highlights the roles played by CS Assistant Prof. Joseph Gonzalez and the class Data Science 100.

Three EECS-affiliated papers win Helmholtz Prize at ICCV 2017

Three papers with Berkeley authors received the Helmholtz Prize at the International Conference on Computer Vision (ICCV) 2017 in Venice, Italy.  This award honors  papers that have stood the test of time (more than ten years after first publication) and is bestowed by the IEEE technical committee on Pattern Analysis and Machine Intelligence (PAMI).    Seven papers won this year, among them: "Recognizing action at a distance," by A Efros, A Berg, G Mori and J Malik, ICCV 2003; "Discovering objects and their location in images," by J Sivic, B Russell, A Efros, A Zisserman and W Freeman, ICCV 2005; and "The pyramid match kernel: Discriminative classification with sets of image features," by K Grauman and T Darrell, ICCV 2005."

(photo Tiberio Uricchio)

Caffe team wins Everingham Prize at ICCV 2017

The Caffe team researchers ('13 alumnus and current GSR Yangqing Jia, grad student Evan Shelhamer,  '17 alumnus Jeff Donahue, '15 alumnus Sergey Karayev, grad student Jonathan Long, former postdocs Ross Girshick and Sergio Guadarrama, and Prof. in Residence Trevor Darrell) have been awarded the Mark Everingham Prize at the International Conference on Computer Vision (ICCV) 2017.  Caffe is a deep learning framework made with expression, speed, and modularity in mind,  developed by Berkeley AI Research (BAIR) and by community contributors. The Everingham Prize is bestowed by the IEEE technical committee on Pattern Analysis and Machine Intelligence (PAMI) and is given to individuals or groups "who have made a selfless contribution of significant benefit to other members of the computer vision community."  The Caffe team won "for providing an open-source deep learning framework that enabled the community to use, train and share deep convolutional neural networks. Caffe has had a huge impact, both academic and commercial. "
Mattel Kamigami (TechCrunch)

Mattel releases Dash foldable robot bugs

Mattel has launched a line of biologically inspired foldable robot bugs designed in collaboration with Dash Robots, a spin-off of the Biomimetic Millisystems Lab (BML).  The researchers at BML, under the direction of Prof. Ron Fearing, draw inspiration from nature to build more efficient robotics.  The new toys, called  Kamigami, let kids build their own robotic bugs, like mantises, ladybugs and scorpions.  Each $50 kit contains parts of a six-legged robot (with an accelerometer, gyroscope, and IR transmitter/receiver) and foldable plastic origami sheets to transform each robot into a different creature.

Rebecca Chery presenting her project (photo: Daniel McGlynn)

Rebecca Chery meets PREP design challenge

The experiences of EECS freshman Rebecca Chery, a participant in the Pre-Engineering Program (PREP), are described in a Berkeley Engineering article titled "PREP by design."  PREP is a three-week program that gives incoming engineering majors a head start on academics, networking and professional development. Chery's team used equipment at the Jacobs Institute makerspace to create a phone case with a keyfob inside that would trigger a door to open once the phone case detected a sensor in close proximity. The prototype was chosen by the PREP students as their favorite project from the design challenge.

Berkeley DeepDrive Releases 36,000 Nexar Videos to Research Community

Berkeley DeepDrive (BDD) and Nexar announced the release of 36,000 high frame-rate videos of driving, in addition to 5,000 pixel-level semantics-segmented labeled images, and invited public and private institution researchers to join the effort to develop accurate automotive perception and motion prediction models.  The BDD Industry Consortium, led by EE Prof. Trevor Darrell , investigates state-of-the-art technologies in computer vision and machine learning for automotive applications. Nexar, as a member of the consortium, contributes video and images captured by its road safety AI camera application deployed in over 100 countries worldwide.  The Nexar driving data will be used for academic research (for activities like training and validating models for real world applications) as well as open crowdsourced research challenges based on parts of the driving data.

Bryan Catanzaro talks AI

EECS alumnus Bryan Catanzaro (Ph.D. '11) is interviewd by Byron Reese for episode 13 of his series Voices in AI.  Catanzaro, who is the head of Applied AI Research at NVIDIA, discusses sentience, transfer learning, speech recognition, autonomous vehicles, and economic growth.  "I like to think about artificial intelligence as making tools that can perform intellectual work.  Hopefully, those are useful tools that can help people be more productive in things that they need to do," he says.

OSA Honorary Member Amnon Yariv

Amnon Yariv named 2017 Honorary Member of the Optical Society

EE alumnus Amnon Yariv (B.S '54/M.S. '56/Ph.D. '58) has been named a 2017 Honorary Member of the Optical Society (OSA).  Honorary Membership is the most distinguished of all OSA Member categories and is awarded to individuals who have made unique, seminal contributions to the field of optics.  Yariv was elected for pioneering scientific and engineering contributions to photonics and quantum electronics that have profoundly impacted lightwave communications and the field of optics as a whole. His research has focused on creating the mathematical tools and building blocks underpinning guided wave optics, the backbone of today's optoelectronic technologies. This endeavor led to the proposal and demonstration of the distributed feedback laser -- the main light source and information carrier of internet traffic -- and started the field of optoelectronic integrated circuits.  Yariv, who is currently a professor at the California Institute of Technology, received the National Medal of Science in 2010.

A chick embryo with birth defects (Science Signaling)

Chunlei Liu's research may help prevent birth defects linked to fever during early pregnancy

EE Associate Prof. Chunlei Liu has co-authored a study which has identified a specific molecular pathway that links maternal fever early in pregnancy to some congenital heart and cranial facial birth defects.  The findings, which were published in the journal Science Signaling, suggest a portion of congenital birth defects could be prevented if fevers are treated through the judicious use of acetaminophen during the first trimester.  Among their discoveries, the scientists found that neural crest cells—which are critical building blocks for the heart, face and jaw—contain temperature-sensitive properties.  “With electrical magnetic waves coupled with engineered ion channel proteins, we are able to impact specific biological cells remotely without affecting other biochemical environments,” Liu said. “The technique can be applied to study many different cell types and their roles at various developmental stages.”  The research was conducted in collaboration with scientists at Duke Universiy.

RISELab researchers investigate how to build more secure, faster AI systems

Computer Science faculty in the Real-Time Intelligent Secure Execution Lab (RISELab) have outlined challenges in systems, security and architecture that may impede the progress of Artificial Intelligence, and propose new research directions to address them.  The paper, A Berkeley View of Systems Challenges for AI, was authored by Profs. Stoica, Song, Popa, Patterson, Katz, Joseph, Jordan, Hellerstein, Gonzalez, Goldberg, Ghodsi, Culler and Abbeel, as well as Michael  Mahoney in Statistics/ICSI. Some of the challenges outlined include AI systems that make timely and safe decisions in unpredictable environments, that are robust against sophisticated adversaries, and that can process ever increasing amounts of data across organizations and individuals without compromising confidentiality.