research

Ling-Qi Yan helps to improve computer rendering of animal fur

CS graduate student Ling-Qi Yan (advisors: Ravi Ramamoorthi/Ren Ng) and researchers at U.C. San Diego are the subject of an article in TechXplore titled "Scientists improve computer rendering of animal fur."  He is part of a team that developed a method for dramatically improving the way computers simulate fur, and more specifically, the way light bounces within an animal's pelt.  The researchers are using a neural network to apply the properties of a concept called subsurface scattering to quickly approximate how light bounces around fur fibers.  The neural network only needs to be trained with one scene before it can apply subsurface scattering to all the different scenes with which it is presented. This results in simulations running 10 times faster than current state of the art.  "We are converting the properties of subsurface scattering to fur fibers," said Yan. "There is no explicit physical or mathematical way to make this conversion. So we needed to use a neural network to connect these two different worlds."  The researchers recently presented their findings at the SIGGRAPH Asia conference in Thailand.

Dan Wallach to testify about election security and voting machines in Texas

EECS alumnus Dan Wallach (B.S. '93) will testify before the Texas Senate Select Committee on Election Security at a hearing about recent election irregularities in Texas, a review of voting security protocols and the responsibilities and duties of members of the Electoral College.  Specifically, the hearing will examine the use of electronic voting machines and paper ballots, voting fraud and disenfranchisement occurring inside nursing homes and assisted living facilities, outside interference and manipulation of elections, and the voting requirements of presidential electors.  Wallach is widely regarded as an expert on voting machine security.  He is currently an EECS professor at Rice University and a scholar at Rice's Baker Institute for Public Policy. 

Security for data analytics – gaining a grip on the two-edged sword

Prof. Dawn Song and graduate student Noah Johnson are taking a new approach to enable organizations to follow tight data security and privacy policies while enabling flexible data analysis, as well as machine learning for analysts.  Working with Uber, they tested their system using a dataset of 8 million queries written by the company’s data analysts. The system is currently being integrated into Uber’s internal data analytics platform.  With help from the Signatures Innovation Fellows program, they are advancing the system to provide the same level of security and flexibility for a broad range of data analysis and machine learning, whether needed in basic and medical research or business analytics.

Anca Dragan and Raluca Popa

Anca Dragan and Raluca Popa win Sloan Research Fellowships

Assistant Profs. Anca Dragan and Raluca Ada Popa have been awarded 2018 Alfred P. Sloan Research Fellowships.  They are among 126 early-career scholars who represent the most promising scientific researchers working today. Their achievements and potential place them among the next generation of scientific leaders in the U.S. and Canada. Winners receive $65,000, which may be spent over a two-year term on any expense supportive of their research.  Popa and Dragan were both selected in the Compter Science category.   Popa is a co-founder of the RISELab where she is trying to develop a learning and analytics framework that can run on encrypted data.  Dragan runs the InterACT lab and is a PI for the Center for Human-Compatible AI.  Her goal is to enable robots to work with, around and in support of people, autonomously generating behavior in a way that formally accounts for their interactions with humans. “The Sloan Research Fellows represent the very best science has to offer,” said foundation president Adam Falk. “The brightest minds, tackling the hardest problems, and succeeding brilliantly – fellows are quite literally the future of 21st century science.”

Computer Vision to Protect Patients — and Budgets

Prof. Alexandre Bayen and PhD student Pulkit Agrawal developed a computer vision-based system to help memory care centers monitor patient falls and to reduce them where possible.  State regulations require an MRI of the head any time a patient suffers an unwitnessed fall, and about a fourth of all Alzheimer’s-related hospital visits are triggered by a fall. With five million Americans currently living with Alzheimer’s, the task of preventing, tracking and treating fall-related injuries has become daunting and costly, with more than a $5 billion annual cost to medicare--and the number of people with Alzheimer’s is expected to double in the next 15 years.   A system capable of detecting falls by autonomously monitoring patients and sending therapists video clips could improve the monitoring process immensely  “There are no effective drugs yet to treat Alzheimer’s,” Agarwal says. “Until we have them, we have to help patients where they are. Developing computer vision systems to detect falls and fall vulnerability seemed like a good way to improve healthcare for a growing patient population.”

Constance Chang-Hasnain and David Tse elected members of the National Academy of Engineering

Prof. Constance Chang-Hasnain and Adjunct Prof. David Tse have been elected members of the National Academy of Engineering (NAE).   Election to the NAE is among the highest professional distinctions accorded to an engineer.  Academy membership honors those who have made outstanding contributions to "engineering research, practice, or education, including, where appropriate, significant contributions to the engineering literature" and to "the pioneering of new and developing fields of technology, making major advancements in traditional fields of engineering, or developing/implementing innovative approaches to engineering education."  Chang-Hasnain was elected "for contributions to wavelength tunable diode lasers and multiwavelength laser arrays."  Tse was elected "for contributions to wireless network information theory."    37 of the 2,293 current U.S. members are EECS faculty.

Jiawang Nie wins the 2018 SIAM Activity Group on Linear Algebra Best Paper Prize

Alumnus Jiawang Nie (Ph.D. '06, co-advisors: James Demmel and Bernd Sturmfels) has won the 2018 Best Paper Prize from the Society for Industrial and Applied Mathematics (SIAM) Activity Group on Linear Algebra (SIAG/LA).  His paper, Generating Polynomials and Symmetric Tensor Decompositions, Foundations of Computational Mathematics, was deemd the most outstanding paper, as determined by the prize committee, on a topic in applicable linear algebra published in English in a peer-reviewed journal.  8 out of 11 of the previous awards, which are  chosen every 3 years, have gone to EECS faculty, postdocs, and graduate students.  Nie is now a Professor of Mathematics at the University of California, San Diego.  He will present his work in Hong Kong on May 4-8 at the SIAM Conference on Applied Linear Algebra (SIAM-ALA18).

Laura Waller wins 2018 SPIE Early Career Achievement Award

Associate Prof. Laura Waller has won the 2018 Early Career Achievement Award--Academic focus--from the International Society for Optics and Photonics (SPIE). The award, which is paired with an industry-focused award, is presented annually in recognition of significant and innovative technical contributions in the engineering or scientific fields of relevance to SPIE.  Waller, who heads the Computational Imagaing Lab, was recognized for "her contributions to biomedical and industrial science through development of computational imaging hardware and software for phase retrieval, 3D imaging and partially coherent systems."  The award was presented at the Opto Symposium, co-chaired by colleague Prof. Connie Chang-Hasnain, on January 29th,

Avideh Zakhor named Electronic Imaging Scientist of the Year

Prof. Avideh Zakhor has been named 2018 Electronic Imaging Scientist of the Year by the Society for Imaging Science and Technology.  She was cited “for her significant contributions to signal processing, including 3D image processing & computer vision, 3D reality capture systems,  3D modeling, mapping and positioning,  image and video compression and communication.”  Zakhor and her team drove a truck loaded with sensors around Berkeley, and flew in a helicopter overhead, to gather imagery, and map part of the city in three dimensions. She eventually sold her research to Google, which built her innovations into Google Earth and Street View, used it to advance Google Maps, and is pushing it forward into a future of self-driving cars.  This award is given annually at the EI Symposium to a member of the electronic imaging community who who has demonstrated excellence and commanded the respect of his/her peers by making significant and substantial contributions to the field of electronic imaging via research, publications, or service.

Alex Bayen on why traffic apps make congestion worse

Prof. Alexandre Bayen, director of UC Berkeley’s Institute of Transportation Studies, is working on smarter traffic apps that will talk to one another to prevent clogged freeways and city streets.  When Bayen spoke at the Cal Future Forum in 2017, he described how UC Berkeley transportation researchers are developing the science and technology to “enable collaboration both at the commuter level — you and me — and the city level.”  Since “we can’t build our way out of congestion,” he says, the only way this will work is if the apps collaborate and steer different people along different routes to prevent congestion.