School of Engineering
Showing 5,001-5,100 of 5,933 Results
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Jay Prakash Thakur
Graduate, Stanford Center for Professional Development
BioJay Prakash Thakur is a Senior Machine Learning Engineer at Microsoft specializing in AI agents, multi-agent systems, and responsible agentic AI innovation. Featured in WIRED Magazine for insights on AI agent accountability and the Stanford LEAD Quarterly, Jay bridges technical excellence with strategic thinking to shape the future of human-AI collaboration.
As an open-source contributor to leading agentic frameworks and advisor to industry committees, he focuses on building scalable systems that drive business growth while serving society ethically. His deep expertise spans agentic AI architecture, multi-agent systems, big data, deep learning, and machine learning.
Previously built scalable AI/ML solutions at Amazon and Accenture, Jay has published research on frontier technologies and actively contributes to leading tech communities including IEEE (Senior Member), ACM, and AAAI. He serves as a business and startup advisor, holds multiple patents, and is a global speaker, conference session chair, and panelist on Agentic AI innovation and ethics.
With thought leadership articles reaching global readers and trending on major tech platforms, Jay has established himself as a prominent voice shaping the future of agentic AI development at the intersection of innovation, strategic leadership, and responsible technology. -
Hawa Racine Thiam
Assistant Professor of Bioengineering and of Microbiology and Immunology
Current Research and Scholarly InterestsOur current work has two branches. Branch #1 is building a quantitative and predictive understanding of how neutrophils initiate and complete NETosis. Branch #2 is identifying the molecular and biophysical mechanisms that regulate high deformability in neutrophils. These branches converge onto understanding and harnessing the impact of nuclear biophysics on immune cell functions to re-engineer neutrophils for improved health.
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Tristan Thrush
Ph.D. Student in Computer Science, admitted Autumn 2023
BioI'm a Computer Science PhD student at Stanford in the NLP group and AI lab, supervised by Tatsunori Hashimoto and Christopher Potts. Previously, I was a founding member of the technical staff at Contextual AI (a startup working on retrieval augmented generation). Before that, I was a research engineer at Hugging Face. Before that, I was a research associate at Facebook AI Research, supervised by Douwe Kiela and then Adina Williams. And before that, I was a research associate at MIT Brain and Cognitive Sciences, supervised by Roger Levy. I Received my MEng in computer science with a concentration in artificial intelligence under Patrick Winston at the MIT Computer Science and Artificial Intelligence Lab. I received my BS also at MIT in computer science, with a minor in linguistics and a minor in math. While I was an undergrad, I did research with the Perception Systems Group at NASA's Jet Propulsion Lab.
I'm interested in AI. Specifically: natural language processing, computer vision, high-dimensional statistics, and data-centric AI methods. I have done several large-scale projects with a focus on the data side, which is so intertwined with the model side that it is sometimes hard to tell where one ends and the other begins.
Here are three of my favorite papers:
Perplexity Correlations: https://arxiv.org/abs/2409.05816
(This one has some fun math and is useful for pretraining data selection)
Multimodal Evaluation: https://arxiv.org/abs/2204.03162
(This one poses a still open challenge for word-order understanding in vision-language models)
Rover Relocalization for Mars Sample Return: https://ieeexplore.ieee.org/abstract/document/9381709
(There is nothing cooler than robots in space) -
Jakob Thumm
Postdoctoral Scholar, Aeronautics and Astronautics
BioJakob is a postdoctoral scholar in the Department of Aeronautics and Astronautics. His research aims to improve the safety, efficiency, and acceptance of autonomous robots by combining formal methods and machine learning. Jakob focuses on developing algorithms that enable robots to efficiently act in dynamic environments while guaranteeing safety at all times. He is particularly interested in allowing robots to safely work together with humans.
Prior to joining Stanford, Jakob earned his Ph.D. in Computer Engineering from the Technical University of Munich. His doctoral thesis is titled ``Establishing Safe and Preference-Aligned Human-Robot Collaboration in Autonomous Manipulation'' and passed with highest distinctions. Jakob received his M.Sc. and B.Sc. in Mechatronics from the Karlsruhe Institute of Technology, researching the intersection of system modelling and machine learning.
Outside the lab, Jakob is a passionate runner and volunteer at Sutro Stewards, where he maintains hiking trails in the heart of San Francisco. -
Sebastien Tilmans
Student, Civil and Environmental Engineering
BioSebastien is the Executive Director at the Codiga Resource Recovery Center at Stanford University, a test-bed facility dedicated to accelerating the scale-up of innovative resource recovery systems. Prior to joining Stanford, he worked in the Process Engineering group at Oceanside Wastewater Treatment Plant for the San Francisco Public Utilities Commission. He has also designed and implemented several decentralized anaerobic wastewater treatment systems in Panama, and a waterless sanitation service in Haiti. He holds a PhD in Environmental Engineering from Stanford University, and a B.E. in Civil Engineering from Cooper Union. He was a Fulbright scholar, an NDSEG fellow, and an EPA STAR fellow.
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Fouad Tobagi
Professor of Electrical Engineering
BioTobagi works on network control mechanisms for handling multimedia traffic (voice, video and TCP- based applications) and on the performance assessment of networked multimedia applications using user-perceived quality measures. He also investigates the design of wireless networks, including QoS-based media access control and network resource management, as well as network architectures and infrastructures for the support of mobile users, all meeting the requirements of multimedia traffic. He also investigates the design of metropolitan and wide area networks combining optical and electronic networking technologies, including topological design, capacity provisioning, and adaptive routing.
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Alexander Toews
Ph.D. Student in Electrical Engineering, admitted Autumn 2017
Current Research and Scholarly InterestsMagnetic resonance imaging, computational imaging
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Jeffrey B. Tok
Laboratory Director, Chemical Engineering
BioEducation:
The University of Washington, Seattle, WA, B.Sc. (Chemistry & Biochemistry), 1989-1992
The University of Chicago, Chicago, IL, Ph.D. (Bioorganic Chemistry), 1992-1996
Harvard University, Boston, MA, Postdoctoral Research Fellow (Bioorganic Chemistry), 1997-1999
Work Experience:
Assistant Professor, City University of New York, York College and Graduate Center, 1999-2003
Associate Professor, City University of New York, York College and Graduate Center, 2003-2004
Principal Scientist (Indefinite), Lawrence Livermore National Laboratory, 2004-2008
Chief BioScientist, Micropoint Bioscience Inc, 2008-2010
Senior Research Engineer/Scientist, Stanford University, 2010-present
Director, Uytengsu Teaching Center, Shriram Center, 2015-present
Manager, Soft & Hybrid Materials Shared Facility, Stanford Nano Shared Facility, 2010-present
Manager & Instructor, Dept of Chemical Engineering Teaching Lab, 2010-present
Research Activities (via 'Google Scholar'):
https://scholar.google.com/citations?user=hXSGJC0AAAAJ&hl=en&oi=sra -
Alice Tor
Ph.D. Student in Electrical Engineering, admitted Autumn 2022
BioPhD candidate in Electrical Engineering, advised by Dr. Paul Nuyujukian
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George Toye
Adjunct Professor
BioGeorge Toye, Ph.D., P.E., is adjunct professor in Mechanical Engineering at Stanford University.
While teaching advanced project-based engineering design thinking and STEM-based innovations at the graduate level as part of ME310, he also contributes to research in varied topics in engineering education, and effective globally-distributed team collaborations. As well, he remains active in entrepreneurship and varied advising/consulting work.
George earned his B.S. and M.S. degrees in Mechanical Engineering from U.C. Berkeley, and Ph.D. in Mechanical Engineering with minor in Electrical Engineering from Stanford University.
Since 1983, he has enjoyed volunteering annually to organize regional and state-level Mathcounts competitions to promote mathematics education amongst middle-school aged students. -
Simon Treillou
Postdoctoral Scholar, Civil and Environmental Engineering
BioSimon Treillou (he/him) is a postdoctoral researcher at the Baker Coastal Lab at Stanford University, where he studies coastal transport and mixing processes with a focus on wave-driven circulation dynamics. He holds a Master's degree in Applied Mathematics from INSA Toulouse and recently completed his Ph.D. in Coastal Oceanography at the University of Toulouse (France) in the LEGOS lab under the supervision of Patrick Marchesiello. His research uses advanced 3D wave-resolving models to improve the understanding of tracer dispersal in nearshore environments, addressing critical environmental challenges such as contaminant mitigation and ecosystem resilience. Simon's work will integrate numerical modeling, remote sensing, and experimental methods to advance knowledge of coastal physics.
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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, where she leads the High Assurance Computer Architectures Lab. Following her PhD, prior to starting at Stanford, Trippel spent nine months as a Research Scientist at Facebook in the FAIR SysML group. Trippel's research fits broadly in the area of computer architecture and focuses on promoting high assurance—correctness, security, and reliability—as a first-order computer architecture design goal. A central theme of her work is leveraging formal methods, especially automated reasoning, techniques to design and verify hardware systems. Trippel 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; prompted Intel to update their Software Security Guidance to confirm that two Intel microarchitectures satisfy assumptions made by the Seberus Spectre defense that her lab developed; and produced a novel methodology and tool that synthesized two new variants of the famous Meltdown and Spectre attacks. Trippel's research has been recognized with IEEE Top Picks distinctions, a Sloan Research Fellowship, an NSF CAREER Award, the inaugural Google ML and Systems Junior Faculty Award, the Intel Rising Star Faculty Award, an Intel Outstanding Researcher Award, the 2020 ACM SIGARCH/IEEE CS TCCA Outstanding Dissertation Award, the 2020 CGS/ProQuest® Distinguished Dissertation Award in Mathematics, Physical Sciences, & Engineering, and more.
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Nick Troccoli
Lecturer
BioNick Troccoli is a Lecturer in the Stanford Computer Science Department. He started as a full-time lecturer at Stanford in Fall 2018, after graduating from Stanford in June 2018 with Bachelor's and Master's Degrees in Computer Science. He has taught CS106X, CS107, CS110 and CS111. In 2022, 2024 and 2025 he was named to the Tau Beta Pi Teaching Honor Roll. During his undergraduate career, he specialized in Systems, and during his graduate career he specialized in Artificial Intelligence. He was heavily involved in teaching as both an undergraduate and graduate student; he was an undergraduate Section Leader in the CS 198 Section Leading Program, a graduate CA (Course Assistant) for CS 181, the Head TA for CS 106A and CS 106B, and the summer 2017 instructor for CS 106A. In 2017 he was awarded the Forsythe Teaching Award and the Centennial TA Award for excellence in teaching.
