Stanford University
Showing 21-30 of 141 Results
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Moses Charikar
Donald E. Knuth Professor
Current Research and Scholarly InterestsEfficient algorithmic techniques for processing, searching and indexing massive high-dimensional data sets; efficient algorithms for computational problems in high-dimensional statistics and optimization problems in machine learning; approximation algorithms for discrete optimization problems with provable guarantees; convex optimization approaches for non-convex combinatorial optimization problems; low-distortion embeddings of finite metric spaces.
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Yejin Choi
Dieter Schwarz Foundation HAI Professor and Senior Fellow at the Stanford Institute for Human-Centered Artificial Intelligence
BioYejin Choi is the Dieter Schwarz Foundation Professor and Senior Fellow at the Department of Computer Science at Stanford University and the Stanford Institute for Human-Centered Artificial Intelligence (HAI) respectively. Choi is MacArthur Fellow (class of 2022), AI2050 Senior Fellow (class of 2024), and named among Time100 Most Influential People in AI in 2023. In addition, Choi is a co-recipient of 2 Test-of-Time awards and 8 Best and Outstanding Paper Awards at top AI conferences including ACL, ICML, NeurIPS, ICCV, CVPR, and AAAI, the Borg Early Career Award (BECA) in 2018, the inaugural Alexa Prize Challenge in 2017, and IEEE AI’s 10 to Watch in 2016. Choi was a main stage speaker at TED 2023, and a keynote speaker for a dozen conferences across several AI disciplines including ACL, CVPR, ICLR, MLSys, VLDB, WebConf, and AAAI. Her current research interests include fundamental limits and capabilities of large language models, alternative training recipes for language models, symbolic methods for neural networks, reasoning and knowledge discovery, moral norms and values, pluralistic alignment, and AI safety.
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Emma Dauterman
Assistant Professor of Computer Science
BioEmma Dauterman is an assistant professor at Stanford University in the Department of Computer Science. She works at the intersection of systems, security, and applied cryptography to build systems that provide strong security and privacy properties. She was a postdoc at MIT with Henry Corrigan-Gibbs, and before that, she was a PhD student at UC Berkeley advised by Raluca Ada Popa and Ion Stoica. Emma's work has influenced the Signal messaging application, as well as Apple's Enhanced Visual Search. Emma was a runner-up for the ACM SIGSAC Doctoral Dissertation Award and a recipient of the Microsoft Ada Lovelace Research Fellowship and NSF Graduate Research Fellowship.
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David Dill
Donald E. Knuth Professor in the School of Engineering, Emeritus
Current Research and Scholarly InterestsSecure and reliable blockchain technology at Facebook.
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Ron Dror
Cheriton Family Professor and Professor, by courtesy, of Structural Biology and of Molecular & Cellular Physiology
Current Research and Scholarly InterestsMy lab’s research focuses on computational biology, with an emphasis on 3D molecular structure. We combine two approaches: (1) Bottom-up: given the basic physics governing atomic interactions, use simulations to predict molecular behavior; (2) Top-down: given experimental data, use machine learning to predict molecular structures and properties. We collaborate closely with experimentalists and apply our methods to the discovery of safer, more effective drugs.
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John Duchi
Associate Professor of Statistics, of Electrical Engineering and, by courtesy, of Computer Science
Current Research and Scholarly InterestsMy work spans statistical learning, optimization, information theory, and computation, with a few driving goals: 1. To discover statistical learning procedures that optimally trade between real-world resources while maintaining statistical efficiency. 2. To build efficient large-scale optimization methods that move beyond bespoke solutions to methods that robustly work. 3. To develop tools to assess and guarantee the validity of---and confidence we should have in---machine-learned systems.
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Zakir Durumeric
Assistant Professor of Computer Science
BioI am an Assistant Professor of Computer Science. My research brings a large-scale, empirical approach to the study of Internet security, trust, and safety. I am interested in how to protect people against attacks on the Internet ranging from cybercrime and harassment to censorship and disinformation. I am broadly an empiricist: I build systems to measure complex networked ecosystems at scale, which I use to understand real-world behavior, uncover weaknesses and attacks, architect more resilient defenses, and guide public policy.