School of Engineering
Showing 301-380 of 380 Results
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Constantine Sideris
Associate Professor of Electrical Engineering
BioConstantine Sideris is an Associate Professor of Electrical Engineering at Stanford University. Previously, he was an Assistant Professor at the University of Southern California from 2018 to 2025 and an Associate Professor from 2025 to 2026. He received the B.S., M.S., and Ph.D. degrees with honors from the California Institute of Technology in 2010, 2011, and 2017 respectively. He was a visiting scholar at UC Berkeley’s Wireless Research Center from 2013 to 2014. He was a postdoctoral fellow in the departments of Electrical Engineering and Computing and Mathematical Sciences at Caltech from January 2017 to August 2018.
He was the recipient of an ONR YIP award in 2023, an NSF CAREER award in 2021, an AFOSR YIP award in 2020, an AFOSR DURIP award in 2021, the Caltech Leadership Award in 2017, and an NSF graduate research fellowship in 2010. His research is highly interdisciplinary and bridges the fields of bioengineering, medicine, applied mathematics and computation with electrical engineering and physics.
His research interests include analog/RF integrated circuits, photonic integrated circuits, and computational electromagnetics for biomedical and biosensing applications and wireless communications. His current interests in biomedical devices include portable Point-of-Care in-vitro biosensors, wearable devices for real-time monitoring and analysis of biological signals, ingestible “smart” pills, and implantable devices. His current interests in computational electromagnetics include developing fast algorithms for simulating RF and nanophotonic devices and coupling them with efficient optimization algorithms to achieve the automated design of new, high-performance electromagnetic devices. -
Aaron Sidford
Associate 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.
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Karin Sligar
Programs & Administration Manager, Stanford SystemX Alliance
Current Role at StanfordPrograms & Administration Manager, SystemX Alliance
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Olav Solgaard
Audrey S. Hancock Professor in the School of Engineering
BioThe Solgaard group focus on design and fabrication of nano-photonics and micro-optical systems. We combine photonic crystals, optical meta-materials, silicon photonics, and MEMS, to create efficient and reliable systems for communication, sensing, imaging, and optical manipulation.
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Shuran Song
Assistant Professor of Electrical Engineering and, by courtesy, of Computer Science
BioShuran Song is an Assistant Professor of Electrical Engineering at Stanford University. Before joining Stanford, she was faculty at Columbia University. Shuran received her Ph.D. in Computer Science at Princeton University, BEng. at HKUST. Her research interests lie at the intersection of computer vision and robotics. Song’s research has been recognized through several awards, including the Best Paper Awards at RSS’22 and T-RO’20, Best System Paper Awards at CoRL’21, RSS’19, and finalists at RSS, ICRA, CVPR, and IROS. She is also a recipient of the NSF Career Award, Sloan Foundation fellowship as well as research awards from Microsoft, Toyota Research, Google, Amazon, and JP Morgan.
To learn more about Shuran’s work, please visit: https://shurans.github.io/ -
Andrew Spakowitz
Senior Associate Dean for Research and Faculty Affairs, Professor of Chemical Engineering, of Materials Science and Engineering and, by courtesy, of Applied Physics
Current Research and Scholarly InterestsTheory and computation of biological processes and complex materials
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Adrien Specht
Ph.D. Student in Computational and Mathematical Engineering, admitted Spring 2024
BioI'm a PhD student in the Institute for Computational and Mathematical Engineering (ICME) at Stanford University, mentored by Prof. Mignot. My research is at the intersection of artificial intelligence and sleep medicine, focusing on developing predictive models for circadian rhythms and sleep debt from proteomics data. I adopt a problem-oriented approach, selecting methods based on the data and research questions at hand. My techniques range from linear regression to sophisticated deep learning frameworks, aiming to extract maximal insights from the data. I also explore the use of unsupervised and semi-supervised learning, and am interested in the applications of multimodal and foundation models in biology.
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Jenny Suckale
Associate Professor of Geophysics and, Senior Fellow, by courtesy, at the Woods Institute for the Environment
BioMy research group studies disasters to reduce the risk they pose. We approach this challenge by developing customized mathematical models that can be tested against observational data and are informed by community needs through a scientific co-production process. We intentionally work on extremes across different natural systems rather than focusing on one specific natural system to identify both commonalities in the physical processes driving extremes and in the best practices for mitigating risk at the community level. Our current research priorities include volcanic eruptions, ice-sheet instability, permafrost disintegration, induced seismicity and flood-risk mitigation. I was recently awarded the Presidential Early Career Awards for Scientists and Engineers, the highest honor bestowed by the United States Government on science and engineering professionals in the early stages of their independent research careers and the CAREER award from the National Science Foundation.
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Thierry Tambe
Assistant Professor of Electrical Engineering and, by courtesy, of Computer Science
BioThierry Tambe is an Assistant Professor of Electrical Engineering and, by courtesy, of Computer Science, and the William George and Ida Mary Hoover Faculty Fellow at Stanford University. His research centers on co-designing algorithms and hardware—from high-level models down to custom silicon—to enable efficient execution of AI and data-intensive workloads, with memory efficiency as a central theme. His work has been recognized through an NSF CAREER Award, the inaugural Google ML and Systems Junior Faculty Award, an NVIDIA Graduate PhD Fellowship, an IEEE SSCS Predoctoral Achievement Award, and several distinguished paper awards. Previously, Thierry was a visiting research scientist at NVIDIA and an engineer at Intel. He received a B.S. and M.Eng. from Texas A&M University, and a PhD from Harvard University, all in Electrical Engineering.
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Sindy Tang
Associate Professor of Mechanical Engineering, Senior Fellow at the Woods Institute for the Environment and Professor, by courtesy, of Radiology and of Bioengineering
Current Research and Scholarly InterestsProf. Sindy K.Y. Tang develops engineering platforms that measure biological systems and convert these measurements into quantitative datasets. Her research focuses on experimental systems that probe biological processes across cellular and tissue scales, particularly how physical context—geometry, mechanics, and spatial organization—shapes biological function. Current work spans immune diagnostics, spatial tissue sampling for multi-omics analysis, and single-cell perturbation studies.
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Daniel Tartakovsky
Professor of Energy Science Engineering
Current Research and Scholarly InterestsEnvironmental fluid mechanics, Applied and computational mathematics, Biomedical modeling.
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Hamdi Tchelepi
Max Steineke Professor and Senior Fellow at the Precourt Institute for Energy
Current Research and Scholarly InterestsCurrent research activities: (1) model and simulate unstable miscible and immiscible fluid flow in heterogeneous porous media, (2) develop multiscale numerical solution algorithms for coupled mechanics and multiphase fluid flow in large-scale subsurface formations, and (3) develop stochastic solution methods that quantify the uncertainty associated with predictions of fluid-structure dynamics in porous media.
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Caroline Trippel
Assistant Professor of Computer Science and of Electrical Engineering
BioCaroline Trippel is an Assistant Professor in the Computer Science and Electrical Engineering Departments at Stanford University, where she leads the High Assurance Computer Architectures Lab. Following her PhD, prior to starting at Stanford, Trippel spent nine months as a Research Scientist at Facebook in the FAIR SysML group. Trippel's research fits broadly in the area of computer architecture and focuses on promoting high assurance—correctness, security, and reliability—as a first-order computer architecture design goal. A central theme of her work is leveraging formal methods, especially automated reasoning, techniques to design and verify hardware systems. Trippel research has influenced the design of the RISC-V ISA memory consistency model both via her formal analysis of its draft specification and her subsequent participation in the RISC-V Memory Model Task Group; prompted Intel to update their Software Security Guidance to confirm that two Intel microarchitectures satisfy assumptions made by the Seberus Spectre defense that her lab developed; and produced a novel methodology and tool that synthesized two new variants of the famous Meltdown and Spectre attacks. Trippel's research has been recognized with IEEE Top Picks distinctions, a Sloan Research Fellowship, an NSF CAREER Award, the inaugural Google ML and Systems Junior Faculty Award, the Intel Rising Star Faculty Award, an Intel Outstanding Researcher Award, the 2020 ACM SIGARCH/IEEE CS TCCA Outstanding Dissertation Award, the 2020 CGS/ProQuest® Distinguished Dissertation Award in Mathematics, Physical Sciences, & Engineering, and more.
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Madeleine Udell
Assistant Professor of Management Science and Engineering
Current Research and Scholarly InterestsProfessor Udell builds the mathematical and computational foundations needed for
scalable, accessible, and responsible data-driven decisionmaking in high-stakes domains, with impact on challenges in healthcare, finance, marketing, operations, and engineering.
She develops new efficient algorithms to accelerate and automate optimization and data science, and new frameworks that empower users to invoke these algorithms and interpret the resulting decisions. -
Benjamin Van Roy
Professor of Electrical Engineering, of Management Science and Engineering and, by courtesy, of Computer Science
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
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.
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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.
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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 Edge AI, biosensors, information storage and spintronics. His research and inventions span across a variety of areas including Edge AI, magnetic biochips, in vitro diagnostics, cancer biomarkers, magnetic nanoparticles, magnetic sensors, magnetoresistive random access memory, and magnetic integrated inductors.
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Itschak Weissman
Robert and Barbara Kleist Professor in the School of Engineering
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.
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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.
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Keith Winstein
Associate Professor of Computer Science and, by courtesy, of Electrical Engineering
BioKeith Winstein is an associate 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 group’s research has found broader use, including the Mosh tool, the Puffer video-streaming site, the Lepton compression tool, the Mahimahi network emulators, and the gg lambda-computing framework. He has received the SIGCOMM Rising Star Award, the Sloan Research Fellowship, the NSF CAREER Award, the Usenix NSDI Community Award (2020, 2017), the Usenix ATC Best Paper Award, the Applied Networking Research Prize, the 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 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.
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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 member of the National Academy of Engineering and a Fellow of the IEEE. He 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 Principal Investigator of the Microelectronics Commons California-Pacific-Northwest AI Hardware Hub, a consortium of over 60 companies and academic institutions funded by the CHIPS Act. He was a member of the US Department of Commerce Industrial Advisory Committee on microelectronics. He serves on the Executive Committee of the UC Berkeley think tank Technology Competitiveness and Industrial Policy (TCIP) Center. -
S Simon Wong
Professor of Electrical Engineering, Emeritus
BioWong studies the fabrication and design of high-performance integrated circuits.
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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, computation and engineering approaches to biology and medicine. We are particularly interested in questions concerning gene regulation, genome interpretation and their applications to precision medicine.
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Anita Wood
Assistant Director, Professional Programs, Doerr School of Sustainability, Stanford Engineering Center for Global and Online Education
Current Role at StanfordAnita Wood works on both the Stanford Doerr School of Sustainability (SDSS) External Education & Mobilization (EE&M) team and the Stanford Center for Global and Online Education team. She manages product development and program operations for the Stanford Online Energy Innovation and Emerging Technologies Program. Additionally, she oversees the development of courses and programs created by the SDSS EE&M team.
These courses cover a range of topics, including Strategies for Sustainability, Energy Storage, Water and the Circular Economy, the Economics of the Clean Energy Transition, Grid Integration, Electric and Hybrid Vehicles, and Wind, Water, Solar, and Storage for a Sustainable Future. The newest program is designed for board members, equipping them with essential knowledge spanning the science, business, and stewardship of sustainability.
Please follow the links at the right of this page to learn more about each program and all course offerings. -
Jiajun Wu
Assistant Professor of Computer Science and, by courtesy, of Psychology
BioJiajun Wu is an Assistant Professor of Computer Science and, by courtesy, of Psychology at Stanford University, working on computer vision, machine learning, robotics, and computational cognitive science. Before joining Stanford, he was a Visiting Faculty Researcher at Google Research. He received his PhD in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology. Wu's research has been recognized through the IJCAI Computers and Thought Award, the Young Investigator Programs (YIP) by ONR and by AFOSR, the NSF CAREER award, the Okawa research grant, the AI's 10 to Watch by IEEE Intelligent Systems, paper awards and finalists at ICCV, CVPR, SIGGRAPH Asia, ICRA, CoRL, and IROS, dissertation awards from ACM, AAAI, and MIT, the 2020 Samsung AI Researcher of the Year, and faculty research awards from Microsoft, Google, Nvidia, J.P. Morgan, Samsung, Amazon, and Meta.
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Lei Xing
Jacob Haimson and Sarah S. Donaldson Professor and Professor, by courtesy, of Electrical Engineering
Current Research and Scholarly Interestsartificial intelligence in medicine, medical imaging, Image-guided intervention, molecular imaging, biology guided radiation therapy (BGRT), treatment plan optimization
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Renyuan Xu
Assistant Professor of Management Science and Engineering
BioRenyuan Xu is an assistant professor of Management Science and Engineering (MS&E) at Stanford University. Prior to joining Stanford, she held positions at New York University (2024-2025) and the University of Southern California (2021–2024), and was a Hooke Research Fellow at the Mathematical Institute, University of Oxford (2019–2021). She received her Ph.D. in Operations Research from the University of California, Berkeley in 2019. Renyuan's current research interests include mathematical finance, stochastic analysis, stochastic controls and games, and machine learning theory. She received an NSF CAREER Award in 2024, the SIAM Activity Group on Financial Mathematics and Engineering Early Career Prize in 2023, and two JP Morgan AI Faculty Research Awards in 2022 and 2025.
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Yinyu Ye
Kwoh-Ting Li Professor in the School of Engineering, Emeritus
Current Research and Scholarly InterestsMy current research interests include Continuous and Discrete Optimization, Algorithm Development and Analyses, Algorithmic Game/Market Theory and Mechanism-Design, Markov Decision Process and Reinforcement Learning, Dynamic/Online Optimization and Resource Allocation, and Stochastic and Robust Decision Making. These areas have been the unique and core disciplines of MS&E, and extended to new application areas in AI, Machine Learning, Data Science, and Business Analytics.
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Rachel (Yinghao) Zhang
Managing Director of Industry Partnerships, Stanford SystemX Alliance, Electrical Engineering
BioRachel is the Managing Director of Industry Partnerships at SystemX.
As an innovative business leader, Rachel has launched and expanded businesses across the U.S., Asia, and global markets for tech companies including Alibaba, Ant Group, and Microchip.
During her tenure as Senior Advisor at Ant Group, she also incubated a philanthropic initiative to cultivate 10,000 technology leaders over a decade, aiming to bridge the digital divide and drive economic growth in emerging markets.
Rachel is passionate about harnessing technology for good, driving innovation, and bridging industry collaboration to create a broader meaningful impact.
Rachel is a Stanford GSB alumna. -
Chunmei Zhao
Chief Education Solutions Officer, Stanford Engineering Center for Global and Online Education
Current Role at StanfordChief Education Solutions Officer, Stanford Center for Global & Online Education, School of Engineering.