News

Prof. Raluca Ada Popa

Raluca Ada Popa named a visionary in MIT TR's list of 35 Innovators Under 35

Raluca Ada Popa has been named a Visionary in the MIT Technology Review's list of 35 Innovators Under 35.  Popa found a way to make computation on encrypted data practical.  Her systems secure computers by making data indecipherable to intruders instead of just relying on firewalls to keep them out.  She says her encryption techniques allow systems to operate as if they’ve been blindfolded. They’re able to compute on data without actually seeing it—which is opening the cybersecurity field to a host of new applications.  Her innovations are in use by companies like IBM.

Dawn Song and Hany Farid make WIRED25 list of innovators for 2019

CS Profs Dawn Song and Hany Farid are among Wired Magazine's list of 25 People Who Are Racing to Save Us (WIRED25 list of innovators for 2019). Song is the co-founder and CEO of Oasis Labs, a startup built around differential privacy—cryptographic techniques that allow companies to incorporate data into their algorithms without seeing the individual data points.   Song believes blockchain technology can help offer a secure home for data that doesn’t require trusting any one company with the keys to it.   Her system would enable you to copy your medical data to a location where researchers who are working to cure diseases could access it without compromising your privacy.  Farid is a pioneer of image science, having been one of the first to develop methods to detect when digital photos have been manipulated. He is now one of the leading authorities on Deepfakes: images, videos, or audio files fabricated or altered by machine learning.  Lately, Deepfakes have been used to mislead and manipulate the public during politicial elections.  “This used to be a boutique little field, but now we’re defending democracy,” says Farid.

New Course Takes Data Science to the Next Level

A data science course introduced this semester gives students the chance to delve into concepts and research that are rarely, if ever, offered at the undergraduate level. Data 102, which is being taught by CS Prof. Michael Jordan and Statistics Prof. Fernando Perez, builds on earlier data science courses by not only teaching students the “how to” of Data 100 and the “finding patterns” of Data 8, but also the applications, specifically in relation to decision making in the context of other decision makers and sequences of decisions. Students learn to use data to make decisions even when faced with uncertainty.  “There is no other class that brings statistics, computing, and real world problems together in such an embrace” Jordan said.

"Oracle-Guided Component-Based Program Synthesis" wins 2020 ICSE Most Influential Paper Award

The paper "Oracle-Guided Component-Based Program Synthesis," co-authored by alumnus Susmit Jha (M.S./Ph.D. '11), Sumit Gulwani (Ph.D. '05, advisor: George Necula), EECS Prof. Sanjit A. Seshia, and Ashish Tiwari--and part of Susmit Jha's Ph.D. dissertation advised by Sanjit Seshia--will receive the 2020 Most Influential Paper Award by the ACM/IEEE International Conference on Software Engineering (ICSE). ICSE is the premier conference on software engineering and this award recognizes the paper judged to have had the most influence on the theory or practice of software engineering during the 10 years since its original publication. The citation says, in part, that the paper: "...has made a significant impact in Software Engineering and beyond, inspiring subsequent work not only on program synthesis and learning, but also on automated program repair, controller synthesis, and interpretable artificial intelligence."

Using deep learning to expertly detect hemorrhages in brain scans

A computer algorithm co-developed by Vision Group alumnus Weicheng Kuo (Ph.D. '19), post doc Christian Hӓne, their advisor Prof. Jitendra Malik, and researchers at UCSF, bested two out of four expert radiologists at finding tiny brain hemorrhages in head scans, an advance that one day may help doctors treat patients with traumatic brain injuries, strokes and aneurysms.  The algorithm found some small abnormalities that the experts missed, noted their location within the brain, and classified them according to subtype.  The researchers used of a type of deep learning known as a fully convolutional neural network (FCN) to train the algorithm on a relatively small number of images that were packed with data.  Each small abnormality was manually delineated at the pixel level. The richness of this data — along with other steps that prevented the model from misinterpreting random variations, or “noise,” as meaningful — created an extremely accurate algorithm.

Corelight raises $50m for network traffic analysis in the cloud

Corelight, a start-up founded by CS Prof. Vern Paxson, has secured an additional $50 million in Series C financing for its network traffic analysis (NTA) solutions for cybersecurity.  The company has raised a total of $84 million to date, with investment from General Catalyst, Accel, Osage University Partners and Riverbed Technology Co-founder (and former Berkeley CS professor) Steve McCanne. It has more than doubled in size since its Series B in September 2018.  Corelight  is built on an open source framework called Zeek (formerly Bro), which Paxson began developing in 1995.  Zeek is now widely regarded as the gold standard for both network security management (NSM) and NTA, and has been deployed by thousands of organizations around the world.
Alexandra von Meier

Alexandra von Meier explains why locally sourced power may be the solution to California's vulnerable energy grid

EE Adjunct Prof. Alexandra von Meier, who is the director of the CITRIS California Institute for Energy and Environment (CIEE)’s Electric Grid program, is the subject of a Berkeley News interview titled "Our energy grid is vulnerable. Locally sourced power may be the answer."   In light of last week's massive PG&E power outage, Von Meier discusses why the current power grid is a fire hazard, why solar power is not a practical alternative during a power outage, and ways to make the grid safer.  She also explains how one of CIEE's research projects, EcoBlock, which is looking into stand-alone microgrids of electrical generation and storage that could be shared among multiple households on a city block, might offer a possible solution.

Ren Ng weighs in on why your photos are about to get a lot better

CS Prof. Ren Ng is quoted in a New York Times article titled "The Reason Your Photos Are About to Get a Lot Better."  The article describes how computational photography is driving the future of phone cameras.  “Most photos you take these days are not a photo where you click the photo and get one shot,” said Ng. “These days it takes a burst of images and computes all of that data into a final photograph.”  He and his students are researching new techniques in computational photography, like applying portrait-mode effects to videos.  One type of effect could be to set the recorded footage to automatically focus on whomever is speaking.  “These are examples of capabilities that are completely new and emerging in research that could completely change what we think of that’s possible,” said Ng.

How to Stop Superhuman A.I. Before It Stops Us

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).

Pragya Kushwaha wins 2019 IEEE EDS Early Career Award

EECS Postdoctoral researcher Pragya Kushwaha, currently working with Prof. Chenming Hu and Prof. Sayeef Salahuddin in the Berkeley Short-channel IGFET Model (BSIM) group, has won a prestigious 2019 IEEE Electron Devices Society (EDS) Early Career Award.  This award is presented annually to an IEEE EDS member who has made early career contributions to the field.  Kushwaha develops compact models for emerging electronic devices, now considered the industry standard.  The models are used by circuit designers to predict device behavior (i.e., current, power, and noise) to simulate their circuits during design before fabrication. This honor was previously won by BSAC Postdoc Chen Yang in 2010.