School of Engineering
Showing 5,501-5,550 of 6,507 Results
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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 -
Alberto Tono
Ph.D. Student in Civil and Environmental Engineering, admitted Autumn 2021
Ph.D. Minor, Computer Science
Grad RA student-Hourly, Institute for Human-Centered Artificial Intelligence (HAI)BioTono Alberto is a current PhD Student at Stanford under the supervision of Kumagai Professor: Martin Fischer. He is currently exploring ways in which the Convergence between Digital and Humanities can facilitate cross-pollination between different industries within an Ethical Framework focused on augmenting human intelligence.
He served as the Research and Computational Design Leader in Architectural and Engineering organizations, receiving the O1-visa for outstanding abilities with both HOK and HDR. Tono obtained his Masters in Building Engineering - Architecture from the University of Padua and the Harbin Institute of Technology under the supervision of Andrea Giordano, Carlo Zanchetta and Paolo Borin. He has been working in the computational design and deep learning space since 2014. Furthermore, he is improving Building Information Modeling and Virtual Design and Construction (BIM/VDC) workflows within a statistical framework to optimize the sustainability impact of these processes. Hence, Tono is LEED AP certified. He is an international multi-award-winning “hacker” and speaker, and his work within Architecture and Artificial Intelligence brought him to companies in China, the Netherlands, Italy, and California. Thanks to his multidisciplinary approach he worked as Data Scientist and Geometric Deep Learning Researcher at a Physna/Thangs helping to raise over 80 Milion while working on 3D Search and Monocular 3D Shape Retrieval problems.
Currently is focusing on better methodologies for Generative Building Design, centered on capturing design knowledge from the primordial and universal act of Sketching. -
Jack Topper
Graduate, Stanford Center for Professional Development
BioJack Topper is a Scientific Software Engineer at NASA’s Community Coordinated Modeling Center (CCMC), where he designs and operates large-scale scientific data and modeling systems supporting the global space-weather research community. His work focuses on automating high-performance computing workflows, building resilient data pipelines, and translating complex scientific models into reliable, user-facing services.
He collaborates closely with domain scientists to bridge research objectives and production-grade software, and has taken on technical leadership responsibilities spanning system architecture, reliability, and user adoption. His interests sit at the intersection of optimization, decision systems, machine learning, and large-scale infrastructure, with an emphasis on how mathematical models and data-driven methods inform real-world operational decisions.
Jack is currently pursuing Stanford’s Data, Models, and Optimization Certificate through the Stanford Center for Professional Development, including coursework in convex optimization and related decision-science foundations. -
Alice Tor
Ph.D. Student in Electrical Engineering, admitted Autumn 2022
BioPhD candidate in Electrical Engineering, advised by Dr. Paul Nuyujukian
