School of Engineering
Showing 271-280 of 284 Results
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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 build systems to measure complex networked ecosystems, and I use the resulting perspective to understand real-world behavior, uncover weaknesses and attacks, architect and deploy more resilient approaches, 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.
