School of Engineering
Showing 101-124 of 124 Results
Assistant Professor of Management Science and Engineering and of Computer Science
Current Research and Scholarly InterestsMy research interests lie broadly in the optimization, the theory of computation, and the design and analysis of algorithms. I am particularly interested in work at the intersection of continuous optimization, graph theory, numerical linear algebra, and data structures.
Hyongsok Tom Soh
Professor of Radiology (Early Detection), of Electrical Engineering and, by courtesy, of Chemical Engineering and of Bioengineering
BioDr. Soh received his B.S. with a double major in Mechanical Engineering and Materials Science with Distinction from Cornell University and his Ph.D. in Electrical Engineering from Stanford University. From 1999 to 2003, Dr. Soh served as the technical manager of MEMS Device Research Group at Bell Laboratories and Agere Systems. He was a faculty member at UCSB before joining Stanford in 2015. His current research interests are in analytical biotechnology, especially in high-throughput screening, directed evolution, and integrated biosensors.
Professor of Chemical Engineering and of Materials Science and Engineering
Current Research and Scholarly InterestsTheory and computation of biological processes and complex materials
Assistant Professor of Geophysics and, by courtesy, of Civil and Environmental Engineering and Center Fellow, by courtesy, at the Woods Institute for the EnvironmentOn Leave from 04/01/2021 To 06/30/2021
BioBefore joining Stanford in January 2014, I held a position as Lecturer in Applied Mathematics and as a Ziff Environmental Fellow at Harvard. I hold a PhD in Geophysics from MIT and a Master in Public Administration from the Harvard Kennedy School. Prior to joining graduate school, I worked as a scientific consultant for different international organizations aiming to reduce the impact of natural and environmental disasters in vulnerable communities. The goal of my research is to advance our basic understanding and predictive capabilities of complex multi-phase flows that are fundamental to Earth science. I pursue this goal by developing original computational methods customized for the problem at hand. The phenomena I explore range from the microscopic to the planetary scale and space a wide variety of geophysics systems such as volcanoes, glaciers, and magma oceans. I have taught both undergraduate and graduate courses in scientific, planetary evolution, and natural disasters. Since arriving at Stanford in January 2014, I have co-taught GES 118, Understanding Natural Hazards, Quantifying Risk, Increasing Resilience in Highly Urbanized Regions
Associate Professor of Mechanical Engineering, Senior Fellow at the Woods Institute for the Environment and Professor, by courtesy, of Radiology (Precision Health and Integrated Diagnostics)
Current Research and Scholarly InterestsThe long-term goal of Dr. Tang's research program is to harness mass transport in microfluidic systems to accelerate precision medicine and material design for a future with better health and environmental sustainability.
Current research areas include: (I) Physics of droplets in microfluidic systems, (II) Interfacial mass transport and self-assembly, and (III) Applications in food allergy, single-cell wound repair, and the bottom-up construction of synthetic cell and tissues in close collaboration with clinicians and biochemists at the Stanford School of Medicine, UCSF, and University of Michigan.
For details see https://web.stanford.edu/group/tanglab/
Professor of Energy Resources Engineering
Current Research and Scholarly InterestsCurrent research activities include: (1) modeling unstable miscible and immiscible flows in heterogeneous formations, (2) developing multiscale formulations and scalable linear/nonlinear solution algorithms for multiphase flow in large-scale subsurface systems, and (3) developing stochastic approaches for quantifying the uncertainty associated with predictions of subsurface flow performance.
Assistant Professor of Management Science and Engineering
BioUgander'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, statistics, optimization, and algorithm design.
BioJeremy currently leads the d.school's work with organizations as Director of Executive Education. In this role, he advises professionals and organizations on how to imbed the tools of design thinking and cultivate an innovative organizational culture. He also teaches the celebrated d.leadership and LaunchPad classes, advanced d.school courses focused on creating real-world impact with the tools of design.
Jeremy never expected to be a designer. On his 10th birthday, his father asked him what he wanted to be when he grew up. Jeremy replied,”I want to be one of the people who carry boxes with handles.” A little over a decade later, Jeremy became a briefcase-carrying management consultant focusing on economic development. Then, in 2008, the d.school derailed him completely. His time as a student and a fellow at the d.school showed him that “how” he worked was more important than “what” he did. Today, Jeremy is dedicated to helping others along the same path to becoming a designer. He helps people change their deeply-engrained behaviors and discover, as he did, that it is possible for them to make a difference. He does this through teaching as well as through growing alongside his students to become better in his own life and work every day.
Jeremy is the Director of Executive Education at the d.school. He is a graduate of The University of Texas at Austin’s Red McComb’s School of Business (2005) and the Stanford University Graduate School of Business (2009).
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 research focuses on understanding how an agent interacting with a poorly understood environment can learn over time to make effective decisions. He is interested in the design of efficient reinforcement learning algorithms, understanding what is possible or impossible in this domain, and applying the technology toward the benefit of society. 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-edits 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. 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, and the Management Science and Engineering Department's Graduate Teaching Award. 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.
Robert Grimmett Professor in 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.
Jensen Huang Professor of Global Leadership and Professor, by courtesy, of Applied Physics
Current Research and Scholarly Interestsphotonics, quantum technologies, quantum optics, inverse design
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.
Assistant Professor of Electrical Engineering and, by courtesy, of Computer Science
BioGordon Wetzstein is an Assistant 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, machine vision, optics, scientific computing, 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 in the Camera Culture Group 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), 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.
H.-S. Philip Wong
Willard R. and Inez Kerr Bell Professor in the School of Engineering
BioWong joined Stanford in 2004 after 16 years at IBM Research, with appointments as research staff member, Manager, and Senior Manager. While at IBM, he was responsible for shaping and executing IBM's strategy on nanoscale science and technology and silicon technology. His interests are in the area of nanoscale science and technology, semiconductor technology, solid-state devices, and electronic imaging.
His present research covers a broad range of topics including carbon electronics, 2D layered materials, wireless implantable biosensors, directed self-assembly, nanoelectromechanical relays, device modeling, brain-inspired computing, and non-volatile memory devices such as phase change memory and metal oxide resistance change memory.
Wing Hung Wong
Stephen R. Pierce Family Goldman Sachs Professor in 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.
Kwoh-Ting Li Professor in the School of Engineering and Professor, by courtesy, of Electrical Engineering
BioYinyu Ye is currently the Kwoh-Ting Li Professor in the School of Engineering at the Department of Management Science and Engineering and Institute of Computational and Mathematical Engineering and the Director of the MS&E Industrial Affiliates Program, Stanford University. He received the B.S. degree in System Engineering from the Huazhong University of Science and Technology, China, and the M.S. and Ph.D. degrees in Engineering-Economic Systems and Operations Research from Stanford University. Ye's research interests lie in the areas of optimization, complexity theory, algorithm design and analysis, and applications of mathematical programming, operations research and system engineering. He is also interested in developing optimization software for various real-world applications. Current research topics include Liner Programming Algorithms, Markov Decision Processes, Computational Game/Market Equilibrium, Metric Distance Geometry, Dynamic Resource Allocation, and Stochastic and Robust Decision Making, etc. He is an INFORMS (The Institute for Operations Research and The Management Science) Fellow, and has received several research awards including the winner of the 2014 SIAG/Optimization Prize awarded every three years to the author(s) of the most outstanding paper, the inaugural 2012 ISMP Tseng Lectureship Prize for outstanding contribution to continuous optimization, the 2009 John von Neumann Theory Prize for fundamental sustained contributions to theory in Operations Research and the Management Sciences, the inaugural 2006 Farkas prize on Optimization, and the 2009 IBM Faculty Award. He has supervised numerous doctoral students at Stanford who received received the 2015 and 2013 Second Prize of INFORMS Nicholson Student Paper Competition, the 2013 INFORMS Computing Society Prize, the 2008 Nicholson Prize, and the 2006 and 2010 INFORMS Optimization Prizes for Young Researchers. Ye teaches courses on Optimization, Network and Integer Programming, Semidefinite Programming, etc. He has written extensively on Interior-Point Methods, Approximation Algorithms, Conic Optimization, and their applications; and served as a consultant or technical board member to a variety of industries, including MOSEK.