School of Medicine
Showing 141-160 of 540 Results
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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 -
Teresa Wang
Klaus Bensch Professor in Experimental Pathology, Emerita
Current Research and Scholarly InterestsThe main focus of our research is to understand how cells maintain genome integrity by checkpoint mechanisms during chromosome replication.
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Tong Wang
Resident in Pathology
Candidate For Affiliation, Pathology ClinicalBioTong Wang, MD, PhD, is a physician-scientist in clinical pathology with interests in nucleic acid chemical biology, epigenetics, deep learning, and clinically useful tests.
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Tony Wang
Clinical Assistant Professor, Anesthesiology, Perioperative and Pain Medicine
BioTony Wang is a Clinical Assistant Professor in the Department of Anesthesiology, Perioperative, and Pain Medicine at Stanford University School of Medicine. He is a board-certified anesthesiologist and intensivist with clinical expertise in critical care medicine and liver transplant anesthesiology.
Dr. Wang completed his medical school training, anesthesiology residency, and critical care fellowship at the Johns Hopkins School of Medicine. Dr. Wang is deeply committed to medical education and academic innovation. He serves as the Associate Program Director for the Liver Transplant Anesthesiology Fellowship and is the founding director of Stanford's Anesthesiology Critical Care Education for Leaders (ACCEL) program. He is also Director of Residency Engagement for WikiAnesthesia, a comprehensive digital platform designed to serve as an open-access repository of anesthesia knowledge for trainees and practitioners.
Prior to medicine, Dr. Wang worked as a software engineer at Epic Systems, where he developed an appreciation for the intersection of technology and healthcare delivery.
His clinical interests include the perioperative management of complex patients, liver transplant anesthesiology, critical care medicine, and the integration of technology into anesthesiology education. -
Wenjun Wang
Postdoctoral Scholar, Stem Cell Transplantation
Current Research and Scholarly InterestsMy postdoctoral research focuses on investigating novel therapy for childhood leukemias.
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Wenmin Wang
Postdoctoral Scholar, Ophthalmology
Current Research and Scholarly InterestsI am particularly interested in identifying therapeutic strategies for various eye disorders and investigating the mechanisms by which defects in inositol phosphatases lead to the disruption of primary cilia function and eye diseases by using Omics.
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Xinnan Wang
Professor of Neurosurgery
Current Research and Scholarly InterestsMechanisms underlying mitochondrial dynamics and function, and their implications in neurological disorders.
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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. -
Xunda Wang
Basic Life Research Scientist, Neurosurgery
Current Role at StanfordResearch Scientist
