Stanford University
Showing 32,001-32,100 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. -
Robert Tibshirani
Professor of Biomedical Data Science and of Statistics
Current Research and Scholarly InterestsMy research is in applied statistics and biostatistics. I specialize in computer-intensive methods for regression and classification, bootstrap, cross-validation and statistical inference, and signal and image analysis for medical diagnosis.
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Seda Tierney
Professor of Pediatrics (Cardiology)
Current Research and Scholarly InterestsAssessment of vascular health in children by non-invasive modalities
Exercise interventions in children with congenital and acquired heart disease
Use of telehealth to deliver interventions to children with congenital and acquired heart disease
Parentally-acquired echocardiograms
Quality Improvement in Pediatric Echocardiography
Echocardiography and outcomes in congenital heart disease -
Martin Tik
Affiliate, Psychiatry and Behavioral Sciences
BioDr. Tik is a Visiting Scholar at the Stanford Brain Stimulation Lab and Group Leader at the Medical University of Vienna. His research bridges neuroimaging and brain stimulation to uncover mechanisms of therapeutic neuromodulation.
With a background in Biological Psychology and Medical Physics, Dr. Tik has developed innovative methods for integrating Transcranial Magnetic Stimulation with functional Magnetic Resonance Imaging (TMS-fMRI), enabling real-time measurement of stimulation-induced brain activity. His lab (http://tmsfmri.com) advances these tools toward individualized, state-dependent stimulation paradigms and closed-loop applications.
Building on his long-standing collaboration with the Stanford Brain Stimulation Lab, Dr. Tik works closely with Dr. Nolan Williams and colleagues to translate these neurotechnological innovations into clinical research. This ongoing Vienna–Stanford partnership aims to optimize stimulation parameters and dosing strategies for personalized TMS therapy and a better general understanding of brain circuitry in health and disease. -
Sonia Tikoo-Schantz
Assistant Professor of Geophysics and, by courtesy, of Earth and Planetary Sciences
BioI utilize paleomagnetism and fundamental rock magnetism as tools to investigate problems in the planetary sciences. By studying the remanent magnetism recorded within rocks from differentiated planetary bodies, I can learn about core processes that facilitate the generation of dynamo magnetic fields within the Earth, Moon, and planetesimals. Determining the longevities and paleointensities of dynamo fields that initially magnetized rocks also provides insight into the long-term thermal evolution (i.e., effects of secular cooling) of planetary bodies. I also use paleomagnetism to understand impact cratering events, which are the most ubiquitous modifiers of planetary surfaces across the solar system. Impact events produce heat, shock, and sometimes hydrothermal systems that are all capable of resetting magnetization within impactites and target rocks via thermal, shock, and chemical processes. Therefore, I am able to use a combination of paleomagnetic and rock magnetic characterization to investigate shock pressures, temperatures, structural changes, and post-impact chemical alteration experienced by cratered planetary surfaces.
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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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Hemali Vijay Panchal
Clinical Assistant Professor, Medicine
Current Research and Scholarly InterestsQuality Improvement, Patient Safety, Medical Education
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Molly Timmerman
Clinical Assistant Professor (Affiliated), Orthopaedic Surgery
BioDr. Molly Timmerman is board-certified in Physical Medicine and Rehabilitation. She is Affiliated Clinical Assistant Professor of Physical Medicine and Rehabilitation/Orthopedic Surgery. She practices at Veterans Health Administration in Palo Alto, where she is Medical Director of Regional Amputation Center and the Polytrauma Network Site. She specializes in traumatic brain injury, post-traumatic headache management, and amputation medicine.
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Alice Ting
Professor of Genetics, of Biology and, by courtesy, of Chemistry
On Leave from 09/22/2025 To 06/10/2026Current Research and Scholarly InterestsWe develop chemogenetic and optogenetic technologies for probing and manipulating protein networks, cellular RNA, and the function of mitochondria and the mammalian brain. Our technologies draw from protein engineering, directed evolution, computational design, chemical biology, organic synthesis, microscopy, and genomics.
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Daniel SW Ting
Adjunct Clinical Associate Professor, Ophthalmology
BioAssoc Prof Daniel Ting is a senior consultant vitreo-retinal surgeon working in the Singapore National Eye Center (SNEC), an Associate Professor with Duke-NUS Medical School and an Adjunct Clinical Associate Professor and an Innovation Mentor at Stanford University. He is also the Director of Singapore Health Service (SingHealth) AI Office, SNEC Chief Data and Digital Officer, and the Head of AI and Digital Innovation in Singapore Eye Research Institute (SERI). In 2017, Dr Ting was US-ASEAN Fulbright Scholar visiting the Johns Hopkins University Fulbright Scholar to share his expertise in AI and big data in medicine. In addition to that, his research focus span across not only on the technical aspect on machine learning, deep learning, large language models, explainable AI, privacy preserving technologies, but also safe, responsible and ethical clinical AI applications. He is also involved in several international consensus reporting guidelines such as STARD-AI, QUADAS-AI and DECIDE-AI.
To date, Daniel has published >250 publications on peer reviewed, book chapters, educational articles and conference abstracts. Of those, 45 were published in high impact journals (IF >10) such as JAMA, NEJM, Lancet, Nature Medicine, Nature Biomedical Engineering, Lancet Digital Health, Progress in Retinal and Eye Research, Diabetes Care, Nature Digital Medicine, Ophthalmology and etc. As of Aug 2024 (Google Scholar), his current H index: 61, i-10 index: 172 with total citations of >20,000. Dr Ting has received a total of 100M research grants, in which 20 M as a principal investigator, and 80M as co-investigators on AI and digital innovation related projects in health.
Dr Ting serves in several leadership positions at the different AI and eye societies, including the American Academy of Ophthalmology AI and Retina Ophthalmology Technology Assessment committees, and he also chairs the AI and Digital Innovation Standing Committee for the Asia-Pacific Academy of Ophthalmology and Asia-Pacific Vitreo-Retinal Society. He also serves in numerous advisory and editorial boards in the top-tiered digital and medical journals, including Lancet Digital Health, Frontiers in Medicine, Frontiers in Digital Health and Asia-Pacific Journal of Ophthalmology; Section Editor in British Journal of Ophthalmology and Editorial Board Member in Ophthalmology, Ophthalmology Retina, Ophthalmology Science, British Journal of Ophthalmology, Asia-Pacific Journal of Ophthalmology and Retina.
For the accomplishment, Dr Ting was recognized by many top-tiered international AI and ophthalmology societies in winning many prestigious scientific awards, including Tatler Asia Gen T Award (2021), Singapore National Clinician Scientist Award (2021), Asia-Pacific Academy Ophthalmology (APAO) Nakajima Award (2021), Asia-Pacific Vitreo-Retinal Society (APVRS) Ian Constable Award (2021), MICCAI OMIA Prestigious Achievement Award (2020), ARVO Bert Glaser Award for Innovative Research in Retina (2020), USA Macula Society Evangelos Gragoudas Award (2019), APAO Young Ophthalmologist’s Award (2018) and APTOS Young Innovator Award (2017).
In 2022, 2023 and 2024, he is included in the World’s Top 100 Ophthalmology Power list by the Ophthalmologists; and the World’s Top 2% Scientists by the Stanford University world ranking. In 2021, 2022 and 2023, he was consistently ranked top 3 in the deep learning domain over the past decades (2010 – 2023) by the ExpertScape. In 2024, he won the Singapore National Academy of Medicine Young Scientist Award, and also ranked the Top 100 AI Thought Leaders Worldwide with Fei Fei Li, Yan LeCun, Jensen Huang and many others by H20.ai.
