School of Medicine


Showing 341-360 of 367 Results

  • Tao Wang (王韬)

    Tao Wang (王韬)

    Director of Precision Diabetes Care, Genetics

    Current Role at StanfordPrincipal Investigator, AI for Precision Diabetes Management
    Project Manager & Scientific Co-lead, PsychENCODE Project
    Project Initiator & Clinical Co-lead, Long COVID Clinical RCT with TCM
    Project Initiator & Manager, AI & Wearables Toolkit for Biomedical Sciences
    ENCODE and PsychENCODE Project Data Manager
    Research Scientist, US Veteran Affairs Hospital
    SCGPM HPC System Administrator

  • Tauska Lan

    Tauska Lan

    Affiliate, Genetics - BASE

    BioI'm an ML engineer specializing in LLM post-training and agentic systems—with a particular focus on domains where rigor matters: health, biology, and scientific discovery.

    Long-horizon agents — Designed and shipped multi-step orchestration systems (Pantheon-CLI, OmicVerse Agent) that outperform general SWE-agent baselines on biomedical tasks. Built cross-provider query routing and sandboxed execution to keep complex workflows robust over extended interactions. My agents don't just respond—they plan, recover from failure, and complete real research pipelines end-to-end.

    Agentic science — Created infrastructure where AI doesn't assist research—it conducts it. Vectorized 30 years of NHANES data; parallelized Bayesian kernel machine regression on Kubernetes; built TCGA/GEO pipelines that bridge wet-lab and dry-lab workflows. Co-developed OmicVerse, an open-source platform powering reproducible multi-omics and single-cell analyses across hundreds of studies.

    Experience engineering — Scaled rubric-based reward datasets to 1M+ pairs; trained summary and chain-of-thought reward models via RLAIF/RLHF; delivered measurable benchmark lifts in health AI. I care about the full loop: data curation → reward shaping → careful ablation → verifiable outcome—no cherry-picked demos—just metrics that survive scrutiny.

    Currently pursuing advanced agentic studies at Karolinska Institutet and Stanford!

    Open-source: OmicVerse · Pantheon-CLI · RAG Web UI · AstrBot

    If you're working on post-training at scale, scientific agents, or high-integrity data pipelines—I'm always interested in systems that move from promising results to verifiable outcomes. Let's talk.

  • Shannon White

    Shannon White

    Postdoctoral Scholar, Genetics

    BioHi, I'm Shannon White. I began my postdoctoral fellowship in Michael Snyder's lab in the fall of 2020. I received my PhD from Georgetown University in Tumor Biology in Chunling Yi's lab. My graduate worked explore the signaling and metabolic vulnerabilities of NF2-mutant tumors following YAP/TAZ depletion. My postdoctoral work is exploring the epigenetic hallmarks that contribute to colon cancer progression and drug resistance. I am developing colon organoids derived from pre-cancerous polyp tissue collected from Familial Adenomatous Polyposis patients as a model system to investigate epigenetic and signaling responses to chemoprevention treatments.

  • Monte Winslow

    Monte Winslow

    Associate Professor of Genetics and of Pathology

    Current Research and Scholarly InterestsOur laboratory uses genome-wide methods to uncover alterations that drive cancer progression and metastasis in genetically-engineered mouse models of human cancers. We combine cell-culture based mechanistic studies with our ability to alter pathways of interest during tumor progression in vivo to better understand each step of metastatic spread and to uncover the therapeutic vulnerabilities of advanced cancer cells.

  • John Witte

    John Witte

    Professor of Epidemiology and Population Health, of Biomedical Data Science and of Genetics

    Current Research and Scholarly InterestsThe Witte Lab is a computational and statistical genetics group focused on deciphering the genetic and molecular mechanisms underlying cancer and other complex traits. We undertake integrative analyses across large multi-ancestry cohorts and biobanks, developing and applying methods at the interface of epidemiology, statistical genetics, and machine learning.

  • Yue Wu

    Yue Wu

    Postdoctoral Scholar, Genetics

    Current Research and Scholarly InterestsI built computational methods to integrate and model biological time series, including metabolic dynamics, longitudinal multi-omics data, and micro-sampling. I reduce dimensions, built clusters, and search for causal links.

  • Lei Xiong

    Lei Xiong

    Postdoctoral Scholar, Genetics

    Current Research and Scholarly InterestsMy research focuses on develop deep learning methods to
    1. Infer macrophage-tumor cells interaction using spatial multi-omics
    2. Decipher the cis-regulatory code using a large language models
    3. Predict enhancer-promoter interaction
    4. Multi-omics integration
    5. Build foundational model for single-cell genomics

  • Weize Xu

    Weize Xu

    Postdoctoral Scholar, Genetics

    BioDr. Weize Xu is a postdoctoral researcher in Dr. Xiaojie Qiu's laboratory, where he focuses on advancing computational biology and genomics research. He earned his Ph.D. in Dr. Gang Cao's lab, where he made significant contributions to the development of computational methods and pipelines for spatial transcriptomics (MiP-Seq) and single-cell Hi-C (sciDLO Hi-C). His work during this time centered on enhancing data analysis frameworks, providing more precise insights into complex biological systems.

    Dr. Xu is also an expert in the development of bioimaging processing softwares. During his Ph.D., he developed the U-FISH method, a deep learning-based approach for detecting signal points in FISH images. This innovative project involved curating a high-quality dataset from diverse sources, ensuring robust performance across various FISH data types. The resulting model demonstrated outstanding generalizability and included a user-friendly Web and LLM interface, making it accessible to researchers worldwide.

    In addition to his Ph.D. research, Dr. Xu further honed his skills at SciLifeLab, where he worked under the mentorship of Dr. Wei Ouyang. There, he focused on web programming and developing key components for the Bioimage.IO deep learning platform, gaining valuable experience in creating innovative tools for computational biology.

    With a solid foundation in computational biology, deep learning, and bioinformatics, Dr. Xu is passionate about driving cutting-edge research and contributing new perspectives to his field. He brings a unique combination of technical expertise and a collaborative mindset to his role in Dr. Xiaojie Qiu’s lab.

  • Jielin Yan

    Jielin Yan

    Postdoctoral Scholar, Genetics

    Current Research and Scholarly InterestsI'm interested in understanding how the human genome orchestrates cell fate decisions in development and disease by using high-throughput perturbation and screening methods.

  • Jeehyun Yoe

    Jeehyun Yoe

    Postdoctoral Scholar, Genetics

    Current Research and Scholarly InterestsUncovering and reprogramming molecular circuits guiding tumor-immune interplay