Stanford University
Showing 151-200 of 803 Results
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Jonathan Dotan
Program Coordinator, Electrical Engineering
Staff, Program-Weissman T.BioJonathan Dotan is the founding director of The Starling Lab at Stanford University and USC, where he leads applied research on the decentralized web and human rights. For over 20 years, he’s navigated the intersections of media, tech, and policy as a tech founder.
Jonathan is a fellow at Stanford’s Center for Blockchain Research and Compression Forum, where he is researching strategy and policy for distributed ledger technologies. His scholarship examines Internet governance frameworks, the transition to Web 3.0 and the prospects for a more decentralized internet.
He lectures at Stanford’s School of Engineering and Graduate School of Business. Jonathan’s teaching asks students to consider the never-simple relationship between innovation and progress — recognizing how each new technology brings choices and responsibilities. -
Angelo Dragone
Associate Professor of Photon Science and, by courtesy, of Electrical Engineering
BioAngelo Dragone is an Associate Professor of Photon Science and Electrical Engineering (by courtesy). He has over 20 years of experience in the research and development of Instrumentation for Scientific experiments. He received his Ph.D. in Microelectronics from the Polytechnic University of Bari, Italy, for his research on mixed-signal readout architecture for radiation detectors, conducted at Brookhaven National Laboratory. He worked in the Instrumentation Division at Brookhaven National Laboratory from 2004, before joining SLAC National Accelerator Laboratory in 2008. Over the past 15 years, he has been designing radiation detectors, with a focus on innovative architectural solutions for state-of-the-art scientific instruments and sensor interfaces. These solutions have applications in photon science, particle physics, medical imaging, and national security. At SLAC, he focused his research on designing high frame rate, large dynamic range X-ray detectors for the Linac Coherent Light Source SLAC X-ray Free-electron Laser facility. Since 2012, he has held a management position as head of the Integrated Circuits Department within the Instrumentation Division of the Technology Innovation Directorate (TID) at SLAC. During the past three years, Dr. Dragone has been working on the strategic R&D planning for the SLAC X-ray detectors Initiative and leads, as Program Director, TID Detector R&D, and the applied Microelectronics program. Recently, he has been appointed as Deputy Associate Lab Director for TID strategy. His current research interests are on ultra-fast X-ray detector architectures for X-ray Free-Electron Lasers applications and developing efficient, scalable systems with "smart" real-time processing capabilities. More broadly, he is interested in understanding the fundamental performance limits of radiation detection systems.
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Shaul Druckmann
Associate Professor of Neurobiology, of Psychiatry and Behavioral Sciences and, by courtesy, of Electrical Engineering
Current Research and Scholarly InterestsOur research goal is to understand how dynamics in neuronal circuits relate and constrain the representation of information and computations upon it. We adopt three synergistic strategies: First, we analyze neural circuit population recordings to better understand the relation between neural dynamics and behavior, Second, we theoretically explore the types of dynamics that could be associated with particular network computations. Third, we analyze the structural properties of neural circuits.
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John Duchi
Associate Professor of Statistics, of Electrical Engineering and, by courtesy, of Computer Science
Current Research and Scholarly InterestsMy work spans statistical learning, optimization, information theory, and computation, with a few driving goals: 1. To discover statistical learning procedures that optimally trade between real-world resources while maintaining statistical efficiency. 2. To build efficient large-scale optimization methods that move beyond bespoke solutions to methods that robustly work. 3. To develop tools to assess and guarantee the validity of---and confidence we should have in---machine-learned systems.
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Robert Dutton
Robert and Barbara Kleist Professor in the School of Engineering, Emeritus
BioDutton's group develops and applies computer aids to process modeling and device analysis. His circuit design activities emphasize layout-related issues of parameter extraction and electrical behavior for devices that affect system performance. Activities include primarily silicon technology modeling both for digital and analog circuits, including OE/RF applications. New emerging area now includes bio-sensors and the development of computer-aided bio-sensor design.
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Oskar Nils Leon Eden Wallberg
Graduate Visiting Researcher Student, Electrical Engineering
BioVisiting Student Researcher at Stephen P. Boyd's Lab, Departement of Electrical Engineering, Stanford University
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Abbas El Gamal
Hitachi America Professor in the School of Engineering and Senior Fellow at the Precourt Institute for Energy
BioAbbas El Gamal is the Hitachi America Professor in the School of Engineering and Professor in the Department of Electrical Engineering at Stanford University. He received his B.Sc. Honors degree from Cairo University in 1972, and his M.S. in Statistics and Ph.D. in Electrical Engineering both from Stanford University in 1977 and 1978, respectively. From 1978 to 1980, he was an Assistant Professor of Electrical Engineering at USC. From 2003 to 2012, he was the Director of the Information Systems Laboratory at Stanford University. From 2012 to 2017 he was Chair of the Department of Electrical Engineering at Stanford University. His research contributions have been in network information theory, FPGAs, and digital imaging devices and systems. He has authored or coauthored over 230 papers and holds 35 patents in these areas. He is coauthor of the book Network Information Theory (Cambridge Press 2011). He has received several honors and awards for his research contributions, including the 2016 Richard W. Hamming Medal, the 2012 Claude E. Shannon Award, and the 2004 INFOCOM Paper Award. He is a member of the U.S. National Academy of Engineering and a Fellow of the IEEE. He has co-founded and served on the board of directors and advisory boards of several semiconductor and biotechnology startup companies.
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Dawson Engler
Associate Professor of Computer Science and of Electrical Engineering
BioEngler's research focuses both on building interesting software systems and on discovering and exploring the underlying principles of all systems.
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Jonathan Fan
Associate Professor of Electrical Engineering and Senior Fellow at the Precourt Institute for Energy
Current Research and Scholarly InterestsOptical engineering plays a major role in imaging, communications, energy harvesting, and quantum technologies. We are exploring the next frontier of optical engineering on three fronts. The first is new materials development in the growth of crystalline plasmonic materials and assembly of nanomaterials. The second is novel methods for nanofabrication. The third is new inverse design concepts based on optimization and machine learning.
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Shanhui Fan
Joseph and Hon Mai Goodman Professor of the School of Engineering, Senior Fellow at the Precourt Institute for Energy and Professor, by courtesy, of Applied Physics
BioFan's research interests are in fundamental studies of nanophotonic structures, especially photonic crystals and meta-materials, and applications of these structures in energy and information technology applications
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Chelsea Finn
Assistant Professor of Computer Science and of Electrical Engineering
BioChelsea Finn is an Assistant Professor in Computer Science and Electrical Engineering at Stanford University, and the William George and Ida Mary Hoover Faculty Fellow. Professor Finn's research interests lie in the ability to enable robots and other agents to develop broadly intelligent behavior through learning and interaction. Her work lies at the intersection of machine learning and robotic control, including topics such as end-to-end learning of visual perception and robotic manipulation skills, deep reinforcement learning of general skills from autonomously collected data, and meta-learning algorithms that can enable fast learning of new concepts and behaviors. Professor Finn received her Bachelors degree in Electrical Engineering and Computer Science at MIT and her PhD in Computer Science at UC Berkeley. Her research has been recognized through the ACM doctoral dissertation award, the Presidential Early Career Award for Scientists and Engineers, and the MIT Technology Review 35 under 35 list, and her work has been covered by various media outlets, including the New York Times, Wired, and Bloomberg. Throughout her career, she has sought to increase the representation of underrepresented minorities within CS and AI by developing an AI outreach camp at Berkeley for underprivileged high school students, a mentoring program for underrepresented undergraduates across three universities, and leading efforts within the WiML and Berkeley WiCSE communities of women researchers.
