School of Engineering


Showing 1-10 of 14 Results

  • Brian A. Wandell

    Brian A. Wandell

    Isaac and Madeline Stein Family Professor and Professor, by courtesy, of Electrical Engineering, of Ophthalmology and at the Graduate School of Education

    Current Research and Scholarly InterestsModels and measures of the human visual system. The brain pathways essential for reading development. Diffusion tensor imaging, functional magnetic resonance imaging and computational modeling of visual perception and brain processes. Image systems simulations of optics and sensors and image processing. Data and computation management for reproducible research.

  • Adam Wang

    Adam Wang

    Assistant Professor of Radiology and, by courtesy, of Electrical Engineering

    BioMy group develops technologies for advanced x-ray and CT imaging, including artificial intelligence for CT acquisition, reconstruction, and image processing; novel system and detector designs; spectral imaging; model-based image reconstruction; and radiation transport methods. I am also the Director of the Zeego Lab and the Tabletop X-Ray Lab.

    I completed my PhD in Electrical Engineering at Stanford under the supervision of Dr. Norbert Pelc, developing strategies for maximizing the information content of dual energy CT and photon counting detectors. I then pursued a postdoc at Johns Hopkins with Dr. Jeff Siewerdsen in Biomedical Engineering, developing reconstruction and registration methods for x-ray based image-guided surgery. Prior to returning to Stanford in 2018, I was a Senior Scientist at Varian Medical Systems, developing x-ray/CT methods for image-guided radiation therapy.

  • Shan X. Wang

    Shan X. Wang

    Leland T. Edwards Professor in the School of Engineering and Professor of Electrical Engineering and, by courtesy, of Radiology (Molecular Imaging Program at Stanford)
    On Partial Leave from 04/01/2022 To 06/30/2022

    Current Research and Scholarly InterestsShan Wang was named the Leland T. Edwards Professor in the School of Engineering in 2018. He directs the Center for Magnetic Nanotechnology and is a leading expert in biosensors, information storage and spintronics. His research and inventions span across a variety of areas including magnetic biochips, in vitro diagnostics, cancer biomarkers, magnetic nanoparticles, magnetic sensors, magnetoresistive random access memory, and magnetic integrated inductors.

  • Itschak Weissman

    Itschak Weissman

    Professor of Electrical Engineering
    On Partial Leave from 10/01/2021 To 06/30/2022

    BioTsachy's research focuses on Information Theory, Data Compression and Communications, Statistical Signal Processing, Machine Learning, the interplay between them, and their applications, with recent focus on applications to genomic data compression and processing. He is inventor of several patents and involved in several companies as member of the technical board. IEEE fellow, he serves on the board of governors of the information theory society as well as the editorial boards of the Transactions on Information Theory and Foundations and Trends in Communications and Information Theory. He is founding Director of the Stanford Compression Forum.

  • Gordon Wetzstein

    Gordon Wetzstein

    Associate Professor of Electrical Engineering and, by courtesy, of Computer Science

    BioGordon Wetzstein is an Associate Professor of Electrical Engineering and, by courtesy, of Computer Science at Stanford University. He is the leader of the Stanford Computational Imaging Lab and a faculty co-director of the Stanford Center for Image Systems Engineering. At the intersection of computer graphics and vision, computational optics, and applied vision science, Prof. Wetzstein's research has a wide range of applications in next-generation imaging, display, wearable computing, and microscopy systems. Prior to joining Stanford in 2014, Prof. Wetzstein was a Research Scientist at MIT, he received a Ph.D. in Computer Science from the University of British Columbia in 2011 and graduated with Honors from the Bauhaus in Weimar, Germany before that. He is the recipient of an NSF CAREER Award, an Alfred P. Sloan Fellowship, an ACM SIGGRAPH Significant New Researcher Award, a Presidential Early Career Award for Scientists and Engineers (PECASE), an SPIE Early Career Achievement Award, a Terman Fellowship, an Okawa Research Grant, the Electronic Imaging Scientist of the Year 2017 Award, an Alain Fournier Ph.D. Dissertation Award, and a Laval Virtual Award as well as Best Paper and Demo Awards at ICCP 2011, 2014, and 2016 and at ICIP 2016.

  • Jennifer Widom

    Jennifer Widom

    Frederick Emmons Terman Dean of the School of Engineering, Fletcher Jones Professor of Computer Science and Professor of Electrical Engineering

    BioJennifer Widom is the Frederick Emmons Terman Dean of the School of Engineering and the Fletcher Jones Professor in Computer Science and Electrical Engineering at Stanford University. She served as Computer Science Department Chair from 2009-2014 and School of Engineering Senior Associate Dean from 2014-2016. Jennifer received her Bachelor's degree from the Indiana University Jacobs School of Music in 1982 and her Computer Science Ph.D. from Cornell University in 1987. She was a Research Staff Member at the IBM Almaden Research Center before joining the Stanford faculty in 1993. Her research interests span many aspects of nontraditional data management. She is an ACM Fellow and a member of the National Academy of Engineering and the American Academy of Arts & Sciences; she received a Guggenheim Fellowship in 2000, the ACM SIGMOD Edgar F. Codd Innovations Award in 2007, the ACM-W Athena Lecturer Award in 2015, and the EPFL-WISH Foundation Erna Hamburger Prize in 2018.

  • Bernard Widrow

    Bernard Widrow

    Professor of Electrical Engineering, Emeritus

    Current Research and Scholarly InterestsProf. Widrow's research focuses on adaptive signal processing, adaptive control systems, adaptive neural networks, human memory, and human-like memory for computers. Applications include signal processing, prediction, noise cancelling, adaptive arrays, control systems, and pattern recognition. Recent work is about human learning at the synaptic level.

  • Keith Winstein

    Keith Winstein

    Assistant Professor of Computer Science and, by courtesy, of Electrical Engineering and of Law

    BioKeith Winstein is an assistant professor of computer science and, by courtesy, of electrical engineering at Stanford University. His research group creates new kinds of networked systems by rethinking abstractions around communication, compression, and computing. Some of his research has found broader use, including the Mosh tool, the Puffer video-streaming site, the Lepton compression tool, the Mahimahi network emulators, the gg lambda-computing framework, and the use of a temporal reordering threshold to detect packet loss. His work has received the Sloan Research Fellowship, the Usenix NSDI Community Award (2020, 2017), the Applied Networking Research Prize (2021, 2014), the Usenix ATC Best Paper Award, a Google Faculty Research Award (2017, 2015), a Facebook Faculty Award, the ACM SIGCOMM Doctoral Dissertation Award, and a Sprowls award for best doctoral thesis in computer science at MIT. Winstein previously served as a staff reporter at The Wall Street Journal, was one of the story consultants for HBO’s “Silicon Valley,” and worked at Ksplice, a startup company (now part of Oracle) where he was the vice president of product management and business development and also cleaned the bathroom. He did his undergraduate and graduate work at MIT.