Stanford University


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  • Stefan Thottunkal

    Stefan Thottunkal

    Other Tech - Graduate, Med/Quantitative Sciences Unit
    Graduate Student Employee, Medicine - Primary Care and Population Health

    BioMasters Student in Community Health and Prevention Research, admitted Winter 2025

    Stefan Thottunkal is an Australian medical student, early career researcher and civil servant. His research interests include chronic disease, Native health, and pharmacogenomics. He is particularly interested in pioneering deployment of innovative technologies in clinical settings, utilizing approaches grounded in implementation science. Stefan received an IIE QUAD Fellowship in 2024 to study a Masters of Community Health and Prevention Research at Stanford.

    His current work focuses on precision medicine, advancing implementation of pharmacogenomic testing into clinical practice through leveraging machine learning and large language models to enhance clinical decision-making. He is actively seeking collaboration with those specialised in knowledge-grounded natural language processing and retrieval augmented generation.

    Stefan has worked on high impact initiatives conducted in collaboration with the WHO Global Outbreak and Response Network, Royal Australian College of General Practitioners and National Aboriginal Community Controlled Health Organization. He is passionate about bridging the gap between research, policy, and practice to drive meaningful change.

  • Alex Threlkeld

    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.

  • Zachary D. Threlkeld, MD, FAAN

    Zachary D. Threlkeld, MD, FAAN

    Clinical Associate Professor, Adult Neurology
    Clinical Associate Professor (By courtesy), Neurosurgery

    BioDr. 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.

  • Tristan Thrush

    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)