School of Engineering


Showing 121-130 of 137 Results

  • Madeleine Udell

    Madeleine Udell

    Assistant Professor of Management Science and Engineering and, by courtesy, of Electrical Engineering

    Current Research and Scholarly InterestsProfessor Udell develops new techniques to accelerate and automate data science,
    with a focus on large-scale optimization and on data preprocessing,
    and with applications in medical informatics, engineering system design, and automated machine learning.

  • Johan Ugander

    Johan Ugander

    Associate Professor of Management Science and Engineering

    BioProfessor Ugander's research develops algorithmic and statistical frameworks for analyzing social networks, social systems, and other large-scale data-rich contexts. He is particularly interested in the challenges of causal inference and experimentation in these complex domains. His work commonly falls at the intersections of graph theory, machine learning, statistics, optimization, and algorithm design.

  • Benjamin Van Roy

    Benjamin Van Roy

    Professor of Electrical Engineering, of Management Science and Engineering

    BioBenjamin Van Roy is a Professor at Stanford University, where he has served on the faculty since 1998. His current research focuses on reinforcement learning. Beyond academia, he leads a DeepMind Research team in Mountain View, and has also led research programs at Unica (acquired by IBM), Enuvis (acquired by SiRF), and Morgan Stanley.

    He is a Fellow of INFORMS and IEEE and has served on the editorial boards of Machine Learning, Mathematics of Operations Research, for which he co-edited the Learning Theory Area, Operations Research, for which he edited the Financial Engineering Area, and the INFORMS Journal on Optimization. He received the SB in Computer Science and Engineering and the SM and PhD in Electrical Engineering and Computer Science, all from MIT, where his doctoral research was advised by John N. Tstitsiklis. He has been a recipient of the MIT George C. Newton Undergraduate Laboratory Project Award, the MIT Morris J. Levin Memorial Master's Thesis Award, the MIT George M. Sprowls Doctoral Dissertation Award, the National Science Foundation CAREER Award, the Stanford Tau Beta Pi Award for Excellence in Undergraduate Teaching, the Management Science and Engineering Department's Graduate Teaching Award, and the Lanchester Prize. He was the plenary speaker at the 2019 Allerton Conference on Communications, Control, and Computing. He has held visiting positions as the Wolfgang and Helga Gaul Visiting Professor at the University of Karlsruhe, the Chin Sophonpanich Foundation Professor and the InTouch Professor at Chulalongkorn University, a Visiting Professor at the National University of Singapore, and a Visiting Professor at the Chinese University of Hong Kong, Shenzhen.

  • Andras Vasy

    Andras Vasy

    Robert Grimmett Professor of Mathematics

    Current Research and Scholarly InterestsMy research concentrates on topics in two broad areas of applications of microlocal analysis in which, partly with collaborators, I introduced new ideas in recent years: non-elliptic linear and non-linear partial differential equations (PDE), typically concerning wave propagation or other related phenomena, and inverse problems for X-ray type transforms along geodesics and related problems for determining the metric tensor from boundary measurements.

  • Jelena Vuckovic

    Jelena Vuckovic

    Jensen Huang Professor of Global Leadership, Professor of Electrical Engineering and, by courtesy, of Applied Physics

    Current Research and Scholarly InterestsJelena Vuckovic’s research interests are broadly in the areas of nanophotonics, quantum and nonlinear optics. Her lab develops semiconductor-based photonic chip-scale systems with goals to probe new regimes of light-matter interaction, as well as to enable platforms for future classical and quantum information processing technologies. She also works on transforming conventional photonics with the concept of inverse design, where optimal photonic devices are designed from scratch using computer algorithms with little to no human input. Her current projects include quantum and nonlinear optics, cavity QED, and quantum information processing with color centers in diamond and in silicon carbide, heterogeneously integrated chip-scale photonic systems, and on-chip laser driven particle accelerators.

  • 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)

    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.

  • 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, artificial intelligence, computational optics, and applied vision science, Prof. Wetzstein's research has a wide range of applications in next-generation imaging, wearable computing, and neural rendering systems. Prof. Wetzstein is a Fellow of Optica and the recipient of numerous awards, including 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, an Electronic Imaging Scientist of the Year Award, an Alain Fournier Ph.D. Dissertation Award as well as many Best Paper and Demo Awards.

  • H.-S. Philip Wong

    H.-S. Philip Wong

    Willard R. and Inez Kerr Bell Professor in the School of Engineering

    BioH.-S. Philip Wong is the Willard R. and Inez Kerr Bell Professor in the School of Engineering at Stanford University. He joined Stanford University as Professor of Electrical Engineering in 2004. From 1988 to 2004, he was with the IBM T.J. Watson Research Center. From 2018 to 2020, he was on leave from Stanford and was the Vice President of Corporate Research at TSMC, the largest semiconductor foundry in the world, and since 2020 remains the Chief Scientist of TSMC in a consulting, advisory role.

    He is a Fellow of the IEEE and received the IEEE Andrew S. Grove Award, the IEEE Technical Field Award to honor individuals for outstanding contributions to solid-state devices and technology, as well as the IEEE Electron Devices Society J.J. Ebers Award, the society’s highest honor to recognize outstanding technical contributions to the field of electron devices that have made a lasting impact.

    He is the founding Faculty Co-Director of the Stanford SystemX Alliance – an industrial affiliate program focused on building systems and the faculty director of the Stanford Nanofabrication Facility – a shared facility for device fabrication on the Stanford campus that serves academic, industrial, and governmental researchers across the U.S. and around the globe, sponsored in part by the National Science Foundation. He is the Principal Investigator of the Microelectronics Commons California-Pacific-Northwest AI Hardware Hub, a consortium of over 40 companies and academic institutions funded by the CHIPS Act. He is a member of the US Department of Commerce Industrial Advisory Committee on microelectronics.

  • Wing Hung Wong

    Wing Hung Wong

    Stephen R. Pierce Family Goldman Sachs Professor of Science and Human Health and Professor of Biomedical Data Science

    Current Research and Scholarly InterestsCurrent interest centers on the application of statistics to biology and medicine. We are particularly interested in questions concerning gene regulation, genome interpretation and their applications to precision medicine.