Stanford University
Showing 32,001-32,050 of 37,007 Results
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Caroline Thorn
Scientific Data Curator 2, Biomedical Data Science
Current Role at StanfordScientific curator at ClinPGx
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Evan Thornberry
Head and Curator, David Rumsey Map Center
BioI work to advance teaching, research, and learning with cartographic information and technology.
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Hilary Thorsen
Resource Sharing Librarian, University Libraries
BioI am currently Resource Sharing Libarian in Access Services at Green Library and manage interlibrary loan for Stanford and non-Stanford affiliates, BorrowDirect, and scan-to-PDF services. Formerly, I was Wikimedian-in-Residence as part of the Linked Data for Production (LD4P) project focusing on Wikidata. Prior to that, I served as Metadata Librarian for Humanities in Stanford Libraries.
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Stefan Thottunkal
Other Tech - Graduate, Med/Quantitative Sciences Unit
Graduate Student Employee, Medicine - Primary Care and Population HealthBioStefan Thottunkal is a physician in training, Stanford researcher, and policymaker whose work sits at the intersection of artificial intelligence, precision medicine, translational science, and public health innovation. He completed the M.S. in Community Health and Prevention Research at Stanford University as an IIE Quad Fellow, one of the world’s most selective international research fellowships, where his thesis centered on computational pharmacogenomics and the use of data-driven LLM methods to advance precision prescribing.
His research focuses on translating innovation into clinically meaningful and implementation-ready health solutions, with particular interests in pharmacogenomics, chronic disease, and AI-enabled decision support. He is especially interested in how machine learning and large language models can be used not simply as technical advances, but as robust clinical tools that improve prescribing, strengthen care delivery, and incorporate human centered design principles to effectively integrate precision medicine in routine clinical practice.
At Stanford, he contributes to the Han Lab’s research on advancing precision oncology in advanced non-small cell lung cancer, while helping lead NOURISH, a pioneering Stanford Medicine initiative reimagining cardiometabolic care through culturally tailored nutrition science, behavioral insight, and digital innovation. NOURISH advances a model of lifestyle medicine that preserves cultural relevance while applying rigorous scientific methods to improve metabolic health. By integrating culinary medicine with emerging technologies, the initiative is exploring how AI-enabled tools, personalized digital education, and interactive nutrition support systems can make evidence-based dietary guidance more adaptive, engaging, and scalable across diverse populations. His work in this space reflects a broader interest in how technology can help transform nutrition care from generic advice into a more personalized, culturally tailored, and behaviorally attuned form of preventive medicine.
In parallel with his research career, Stefan brings close to half a decade of experience advising the Australian Federal Government on major health and social policy initiatives. His international experience also includes mentoring hackathon teams in India and medical device development in Nigeria, where he contributed to dialysis device innovation and clinical trials design in resource-constrained settings. Together, these experiences reflect his broader commitment to advancing equitable, evidence-based, and culturally tailored global health innovation. -
Alex Threlkeld
Mathematics, Statistics & Computational Sciences Librarian, Science Library
BioI select print and electronic materials and manage Stanford's subscriptions in my subject areas, I am the liaison between Stanford University Libraries and the Mathematics and Statistics Departments, and I teach Carpentries (and Carpentries-style) workshops on Python, R, and LaTeX. I received a Ph.D. in mathematics from Rice University, with research in knot and link concordance, satellite constructions, and 4-dimensional manifolds, particularly in the topological setting. Before coming to Stanford, I also worked as the Mathematics Collection Development assistant at Rice's Fondren Library.
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Zachary D. Threlkeld, MD, FAAN
Clinical Associate Professor, Adult Neurology
Clinical Associate Professor (By courtesy), NeurosurgeryBioDr. Threlkeld cares for critically ill patients with acute neurologic illness, including traumatic brain injury, stroke, intracerebral hemorrhage, and epilepsy. He completed his residency training in neurology at the University of California, San Francisco, and joined the Stanford Neurocritical Care program after completing fellowship training in neurocritical care at Massachusetts General Hospital and Brigham and Women’s Hospital in Boston. He has a clinical and research interest in traumatic brain injury and disorders of consciousness. In addition, he maintains a strong interest in improvement science, quality improvement, and patient safety.
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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. -
Kumar Thurimella
Resident in Medicine
BioI am an Internal Medicine resident at Stanford in the Translational Investigator Program (TIP), with a planned fellowship in Rheumatology.
I worked as a software engineer at Uber before completing my PhD at the University of Cambridge as a Gates Scholar and my MD at the University of Colorado. My research sits at the intersection of computational biology and B cell immunology, using protein language models and structural AI to identify novel therapeutic targets in autoantibody-mediated diseases.
Outside the clinic and lab, I enjoy skiing, hiking, biking, and reading science fiction. -
Lu Tian
Professor of Biomedical Data Science and, by courtesy, of Statistics
Current Research and Scholarly InterestsMy research interest includes
(1) Survival Analysis and Semiparametric Modeling;
(2) Resampling Method ;
(3) Meta Analysis ;
(4) High Dimensional Data Analysis;
(5) Precision Medicine for Disease Diagnosis, Prognosis and Treatment.
