School of Engineering
Showing 81-90 of 93 Results
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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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David Durst
Ph.D. Student in Computer Science, admitted Autumn 2017
BioDavid is a Computer Science PhD candidate at Stanford University. He's advised by Kayvon Fatahalian and Pat Hanrahan and affiliated with the AHA Agile Hardware Center. His research focuses on programming languages and computer architecture. He's supported by an NSF Graduate Research Fellowship and a Stanford Graduate Fellowship in Science and Engineering. Previously, he worked at BlackRock as a Financial Modeling Group Analyst and received a B.S.E. in Computer Science from Princeton University in 2015.
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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 security, abuse, and misinformation on the Internet. I build systems to measure complex networked ecosystems, and I use the resulting perspective to understand real-world behavior, uncover weaknesses and attacks, architect more resilient approaches, and guide policy decisions.
