School of Engineering
Showing 1,401-1,450 of 6,588 Results
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Junting Duan
Ph.D. Student in Management Science and Engineering, admitted Autumn 2020
BioJunting Duan is a PhD candidate in the Department of Management Science and Engineering (MS&E) at Stanford University. Prior to joining Stanford, she received her B.S. in Mathematics and Applied Mathematics from Peking University in 2020.
Junting's research interests lie broadly in data-driven decision-making, focusing on statistical inference and machine learning, with applications to causal inference and finance. Her research develops new methodologies with rigorous statistical foundations that enable reliable decision-making with complex and imperfect data, and lies at the intersection of (1) statistical learning for high-dimensional data; (2) causal inference; and (3) machine learning for finance and risk management. Her work has been recognized through publications and revisions at top journals including Management Science and the Journal of Econometrics, as well as invitations to present at major conferences such as the American Economic Association Annual Meeting, the NBER-NSF Time-Series Conference, the NBER Forecasting & Empirical Methods Conference, and the INFORMS Annual Meeting.
Visit her personal website for more details: https://juntingduan.com. -
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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Eric Dunham
Professor of Geophysics
Current Research and Scholarly InterestsPhysics of natural hazards, specifically earthquakes, tsunamis, and volcanoes. Computational geophysics.
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Alexander Dunn
Professor of Chemical Engineering
Current Research and Scholarly InterestsMy lab is deeply interested in uncovering the physical principles that underlie the construction of complex, multicellular animal life.
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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.
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Robert Dutton
Robert and Barbara Kleist Professor in the School of Engineering, Emeritus
BioDutton's group develops and applies computer aids to process modeling and device analysis. His circuit design activities emphasize layout-related issues of parameter extraction and electrical behavior for devices that affect system performance. Activities include primarily silicon technology modeling both for digital and analog circuits, including OE/RF applications. New emerging area now includes bio-sensors and the development of computer-aided bio-sensor design.
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Arpit Dwivedi
Masters Student in Aeronautics and Astronautics, admitted Autumn 2024
BioArpit Dwivedi is pursuing his MS in Aeronautics and Astronautics at Stanford University. He received Bachelor of Technology degree in Mechanical Engineering with Honours and with Minor in Artificial Intelligence and Data Science from Indian Institute of Technology Bombay in 2024. His main research interests are in the robot learning, and control of autonomous systems, with an emphasis on self-driving cars, and space vehicles.
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Vijay Prakash Dwivedi
Postdoctoral Scholar, Computer Science
BioVijay Prakash Dwivedi is a Postdoctoral Scholar in Computer Science working on graph representation learning. He holds a PhD from Nanyang Technological University (NTU), Singapore. His work has made contributions to advancing benchmarks for Graph Neural Networks (GNNs), graph positional and structural encodings, and Graph Transformers as universal deep neural networks for graph-based learning. He has also contributed to the integration of parametric knowledge in large language models (LLMs) for diverse applications, particularly in healthcare. Several of the methods he developed during his PhD are now widely adopted in state-of-the-art Graph Transformers and other leading graph learning models. For his research, he received one of the Outstanding PhD Thesis Awards from the NTU College of Computing and Data Science. Vijay has over 7 years experience in both academia and industry with institutions including NTU, Snap Inc., Sony, and ASUS.
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John Eaton
Charles Lee Powell Foundation Professor in the School of Engineering, Emeritus
BioEaton uses experiments and computational simulations to study the flow and heat transfer in complex turbulent flows, especially those relevant to turbomachinery, particle-laden flows, and separated flows, and to develop new techniques for precise control of gas and surface temperature during manufacturing processes.
