School of Engineering
Showing 111-120 of 143 Results
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Yoav Shoham
Professor of Computer Science, Emeritus
BioYoav Shoham is professor emeritus of computer science at Stanford University. A leading AI expert, Prof. Shoham is Fellow of AAAI, ACM and the Game Theory Society. Among his awards are the IJCAI Research Excellence Award, the AAAI/ACM Allen Newell Award, and the ACM/SIGAI Autonomous Agents Research Award. His online Game Theory course has been watched by close to a million people. Prof. Shoham has founded several AI companies, including TradingDynamics (acquired by Ariba), Katango and Timeful (both acquired by Google), and AI21 Labs. Prof. Shoham also chairs the AI Index initiative (www.AIindex.org), which tracks global AI activity and progress, and WeCode (www.wecode.org.il), a nonprofit initiative to train high-quality programmers from disadvantaged populations.
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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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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/ -
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 makes AI and emerging data-intensive applications run efficiently on domain-specific hardware via algorithm-to-silicon co-design. His work has been recognized through a Google ML and Systems Junior Faculty Award, a 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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Li-Yang Tan
Associate Professor of Computer Science
Current Research and Scholarly InterestsTheoretical computer science, with an emphasis on complexity theory
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Brian Trippe
Assistant Professor of Statistics and, by courtesy, of Computer Science
BioDr. Brian Trippe is an assistant professor at Stanford in the Department of Statistics, with an affiliation in Stanford Data Science.
In his research, Dr. Trippe develops probabilistic machine learning methods to address challenges in biotechnology and medicine. Recently, his focus has been on generative modeling and inference algorithms for protein engineering.
Before joining Stanford, Dr. Trippe was a postdoctoral fellow at Columbia University in the Department of Statistics, and a visiting researcher at the Institute for Protein Design at the University of Washington. -
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 working in the area of computer architecture. Prior to starting at Stanford, Trippel spent nine months as a Research Scientist at Facebook in the FAIR SysML group. Her work focuses on promoting correctness and security as first-order computer systems design metrics (akin to performance and power). A central theme of her work is leveraging formal methods techniques to design and verify hardware systems in order to ensure that they can provide correctness and security guarantees for the applications they intend to support. Additionally, Trippel has been recently exploring the role of architecture in enabling privacy-preserving machine learning, the role of machine learning in hardware systems optimizations, particularly in the context of neural recommendation, and opportunities for improving datacenter and at-scale machine learning reliability.
Trippel's 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. Additionally, her work produced a novel methodology and tool that synthesized two new variants of the now-famous Meltdown and Spectre attacks.
Trippel's research has been recognized with IEEE Top Picks distinctions, the 2020 ACM SIGARCH/IEEE CS TCCA Outstanding Dissertation Award, and the 2020 CGS/ProQuest® Distinguished Dissertation Award in Mathematics, Physical Sciences, & Engineering. She was also awarded an NVIDIA Graduate Fellowship (2017-2018) and selected to attend the 2018 MIT Rising Stars in EECS Workshop. Trippel completed her PhD in Computer Science at Princeton University and her BS in Computer Engineering at Purdue University.
