research

Tiffany Chien and Jason Zhou named 2021 Siebel Scholars

EECS 5th Yr Masters students Tiffany Chien and Jason Zhou have been selected for the Siebel Scholars Foundation class of 2021.   They are among 92 distinguished engineering students from the "world’s leading graduate schools of business, computer science, bioengineering, and energy science" to win Siebel Scholars awards this year,  including eight from UC Berkeley.  Siebel Scholars are chosen for their "outstanding academic achievement and demonstrated leadership."  Chien is building a flexible simulation framework for calcium neuron imaging, simulating the 3D physical sample and the lens-less imaging system, and Zhou is interested in swarm intelligence, deep learning and robotics; his research has applications toward defense and disaster relief.

Boubacar Kanté wins 2020 Moore Inventor Fellowship

EECS Associate Prof. Boubacar Kanté has been selected by the Gordon and Betty Moore Foundation to be among its 2020 cohort of Moore Inventor Fellows. The fellowship supports "scientist-inventors who create new tools and technologies with a high potential" to accelerate progress in scientific discovery, environmental conservation and patient care.  Kanté's pioneering work in quantum topological optics includes the invention of the world’s first topological light sources and lasers.   The award will total $825,000 over three years to fund the invention of a new quantum platform that will develop compact sources for robust and energy efficient computing, sensing and imaging using light.

Ana Claudia Arias to participate in new $20M AI food systems research institute

EECS Prof. Ana Claudia Arias has been selected to participate in a new food systems research institute funded by the National Science Foundation (NSF),  US Department of Agriculture (USDA), and the National Institute of Food and Agriculture (NIFA).  The award of $20M over five years will aim to improve US food systems to address issues such as pandemic-driven food system security and safety; improving crop yield, quality and nutrition; decreasing energy and water resource consumption; and increasing production and eliminating food waste.  The objective of the new USDA-NIFA Institute for Artificial Intelligence for Next-Generation Food Systems (AIFS) will focus on the creation of digital replicas of complex food systems, so-called “digital twins,” which can be safely manipulated and optimized in a virtual world and deployed in the physical world afterwards, reducing costs of experiments and accelerating development of new technologies.  A team of ten researchers from the UC Berkeley Next Generation Food Systems Center will combine forces with researchers from five other institutions including UC Davis, Cornell, UIUC, UC ANR, and the USDA, to staff the new center.

Michael Jordan and the implications of algorithmic thinking

CS Prof. Michael I. Jordan is featured in This Week in Machine Learning & AI (TWIML AI) Podcast episode #407 titled "What are the Implications of Algorithmic Thinking? with Michael I. Jordan."   He discusses his current exploration into the intersection of economics and AI, and how machine learning systems could be used to create value and empowerment across many industries through “markets.”  The interview also touches on the potential of “interacting learning systems” at scale, the valuation of data, and the commoditization of human knowledge into computational systems.  Jordan's career, and the ways it has been influenced by other fields like philosophy, is also explored.  Jordan received the 2020 IEEE John von Neumann Medal for "outstanding achievements in computer-related science and technology" earlier this year.

John Davis to participate in BESAC panel on "Black in STEM - in the face of two pandemics"

EECS alumnus John S. Davis II (Ph.D. '00, advisor: Edward Lee) will be participating in the Black Engineering and Science Alumni Club (BESAC)'s homecoming week panel on "Black in STEM -  in the face of two pandemics."  This virtual moderated panel, which will be held on October 17th,  will discuss the impact that both the CoVID-19 pandemic and the events underlying the Black Lives Matter movement have had on the Black community.   Davis is a senior privacy engineer at Google where he has published work to aid CoVID-19 researchers in datamining symptom search terms in Google while simultaneously protecting user privacy.  He joined Google in 2019 after eight years as a senior information scientist at the Rand Corporation, and seven years as a staff researcher at IBM’s Watson Research Center.  The panel will discuss topics ranging from engineering projects by UC Berkeley alumni and faculty to meet the moment of the CoVID-19 pandemic, efforts to address the disparate effects of CoVID-19 on the Black community, and wide-ranging initiatives to redress the impacts of systemic racism.   Registration is required to receive the Zoom log-in.

Gitanjali Swamy is one of the most Influential Indian Women in Technology in 2020

EECS alumna Gitanjali Swamy (Ph.D. '96, advisor: Robert Brayton) has been named one of the most Influential Women in Technology in 2020 by India's Analytics Insight magazine.   She was recognized for "helping enterprises realize their potential through the 'Innovation of Things (IoT).'"  Swamy is the Managing Partner of IoTask, which provides consulting and other advisory services (including a complete methodological guide at the policy and business-planning stage) in areas like Internet of Things, Mobile, and Analytics. She focuses on innovation for environmental, social, governance (ESG) and public-private projects.  Swamy also currently serves as the representative to the EQUALS Coalition of the United Nations, where she chairs the Gender Equitable Investment Working Committee, Research Fellow, and Director at Harvard’s Private Capital Research Institute and the Co-founder of UC Berkeley’s Witi@UC Initiative.  She has founded, built and was Board Director for a number of innovation enterprises, for which she led investment execution from seed stage to over US$1 billion. She was also involved in the formation of MIT’s Opencourseware, the Auto-ID consortium, and the MIT Engine investment vehicle, and has held operating roles at MathWorks and Mentor Graphics.  

Victor Han selected runner-up for ISMRM I.I. Rabi Award

Third year EECS PhD candidate Victor Han (advisor: Prof. Chunlei Liu) was selected as a finalist for the International Society of Magnetic Resonance in Medicine (ISMRM) I.I. Rabi Young Investigator Award for original basic research.  He was chosen for his paper entitled “Multiphoton Magnetic Resonance Imaging,” in which he developed a novel technique that excites multiphoton resonances to generate signal for MRI by using multiple magnetic field frequencies, none of which is near the Larmor frequency. Only the total energy absorbed by a spin must correspond to the Larmor frequency. In contrast, today’s MRI exclusively relies on single-photon excitation. He was named runner-up at the ISMRM annual conference in early August.  Han will continue to develop his multiphoton technique and is exploring its applications in medicine and neuroscience as a part of his PhD dissertation research.  The ISMRM is a multi-disciplinary nonprofit professional association that promotes innovation, development, and application of magnetic resonance techniques in medicine and biology throughout the world. 

Peter Bartlett and Bin Yu to lead $10M NSF/Simons Foundation program to investigate theoretical underpinnings of deep learning

The National Science Foundation (NSF) and the Simons Foundation Division of Mathematics and Physical Sciences are partnering to award $10 million to fund research in the Mathematical and Scientific Foundations of Deep Learning, led by CS Prof. Peter Bartlett and EECS Prof. Bin Yu.  Both professors hold joint appointments in the Department of Statistics.  The researchers hope to gain a better theoretical understanding of deep learning, which is part of a broader family of machine learning methods based on artificial neural networks that digest large amounts of raw data inputs and train AI systems with limited human supervision. Most of the research and education activities will be hosted by the Simons Institute for the Theory of Computing, in the form of structured programs of varying themes.  Other participating institutions will include Stanford, MIT, UCI, UCSD, Toyota Tech in Chicago, EPFL in Switzerland, and the Hebrew University in Israel.

Brian Harvey wins NTLS Education Technology Leadership Award

CS Teaching Prof. Emeritus Brian Harvey has been awarded the National Technology Leadership Summit (NTLS) Education Technology Leadership Award, which recognizes individuals who made a significant impact on the field of educational technology over the course of a lifetime.  The award is NTLS's highest honor.  Harvey wrote the "Computer Science Logo Style" textbook trilogy in the 1980s, which uses the Logo programming language (a subdialect of Lisp which had been created for elementary school children) to teach computer science concepts to more advanced students.   He designed UCBLogo in 1992, a free, open-source programming language that is now the de facto standard for Logo, and won the Berkeley Distinguished Teaching Award in 1995.  He then collaborated with award co-recipient Jens Möenig to develop the block programming language Snap!, which makes advanced computational concepts accessible to nonprogrammers.  It is used in the highly successful class "Beauty and Joy of Computing," which was developed at Berkeley to introduce more diverse audiences to CS. The class is approved for AP credit and, with support from the NSF, has been provided to more than one thousand high school CS teachers nationwide.  Harvey says “Languages in the Logo family, including Scratch and Snap!, take the position that we’re not in the business of training professional computer programmers. Our mission is to bring programming to the masses.”

Ava Tan wins DRC 2020 Best Paper Award

EECS graduate student Ava Jiang Tan (advisor: Sayeef Salahuddin) has won the 2020 Best Paper Award at the 78th Device Research Conference (DRC) for "Reliability of Ferroelectric HfO2-based Memories: From MOS Capacitor to FeFET."  The paper, co-authored by Profs. Salahuddin and Chenming Hu, grad student Yu-Hung Liao, postdoc Jong-Ho Bae, and Li-Chen Wang of MSE, introduces nonvolatile ferroelectric field-effect transistors (FeFETs) which boast impressive programmability and a strong potential for further scalability.  The paper also demonstrates for the first time a systematic, reliable, and rapid method to qualitatively predict the FE endurance of prospective gate stack designs prior to running a full FeFET fabrication process.  Tan works in the Laboratory for Emerging and Exploratory Devices (LEED), and is particularly interested in the architectural potential of nonvolatile ferroelectric CMOS-compatible memories for realizing brain-inspired computing paradigms and energy-efficient hardware for deep learning. The DRC, which is the longest-running device research meeting in the world,  was held in June.