School of Medicine
Showing 351-395 of 395 Results
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Alice Ting
Professor of Genetics, of Biology and, by courtesy, of Chemistry
Current 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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Artem A. Trotsyuk, Ph.D.
Postdoctoral Scholar, Genetics
BioDr. Artem A. Trotsyuk is an AI Fellow in the Department of Genetics at Stanford University and an AI Special Projects Fellow at the Hoover Institution. He earned his PhD in Bioengineering and a Master’s in Computer Science with an AI specialization at Stanford, under the supervision of Dr. Geoffrey Gurtner in the Department of Surgery. He was co-advised by Dr. Zhenan Bao (Chemical Engineering), Dr. Russ Altman (Bioengineering and Medicine), and Dr. Michael Snyder (Genetics). His doctoral research focused on developing a smart bandage that integrates a closed-loop AI processing system for wound sensing and therapeutic delivery. His current work centers on evaluating AI tools in biomedicine, as well as special projects related to security, intent capture, and persona modeling.
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Alexander Eckehart Urban
Associate Professor of Psychiatry and Behavioral Sciences (Major Laboratories and Clinical Translational Neurosciences Incubator) and of Genetics
Current Research and Scholarly InterestsComplex behavioral and neuropsychiatric phenotypes often have a strong genetic component. This genetic component is often extremely complex and difficult to dissect. The current revolution in genome technology means that we can avail ourselves to tools that make it possible for the first time to begin understanding the complex genetic and epigenetic interactions at the basis of the human mind.
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Alun Vaughan Jackson
Postdoctoral Scholar, Genetics
BioCollaborative postdoctoral fellow between the groups of Prof. Michael Bassik (Stanford) and Dr Andreas Puschnik (CZ Biohub) interested in host-virus interactions with the innate immune system.
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Anne Villeneuve
Berthold and Belle N. Guggenhime Professor and Professor of Developmental Biology and of Genetics
Current Research and Scholarly InterestsMechanisms underlying homologous chromosome pairing, DNA recombination and chromosome remodeling during meiosis, using the nematode Caenorhabditis elegans as an experimental system. High-resolution 3-D imaging of dynamic reorganization of chromosome architecture. Role of protease inhibitors in regulating sperm activation.
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Elisa Mariel Visher
Postdoctoral Scholar, Biology
Postdoctoral Scholar, GeneticsCurrent Research and Scholarly InterestsElisa Visher is broadly interested in the (co)evolution of life history strategies, niche breadth, diversification, and adaptability. They use mostly experimental evolution methods in microbial systems to test the predictions and assumptions of theoretical literature. Currently, they am especially interested in understanding the genetics of trade-offs in microbes to better understand patterns of diversity in nature and constraints to adaptation.
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Douglas Vollrath
Professor of Genetics, Emeritus
Current Research and Scholarly InterestsThe Vollrath lab works to uncover molecular mechanisms relevant to the health and pathology of the outer retina. We study metabolic and other cellular interactions between the glial-like retinal pigment epithelium (RPE) and adjacent photoreceptors, with the goals of understanding the pathogenesis of photoreceptor degenerative diseases such as age-related macular degeneration and retinitis pigmentosa, and developing therapies.
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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 -
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. -
Dr. Zhiyong Wang
Visiting Scholar, Genetics
BioDr. Wang is the acting director of the Department of Plant Biology, Carnegie Institution for Science, and a professor by courtesy of the Department of Biology, Stanford University. He is currently an associate editor of Molecular Cellular Proteomics, and editorial board member of Molecular Plant. He is a Fellow of the American Association for the Advancement of Science (AAAS) and recipient of the Humboldt Research Prize.
Dr. Wang obtained his Ph.D. in 1998 from UCLA, where he cloned the plant circadian clock gene CCA1. He did his postdoctoral research at the Salk Institute, where he studied the brassinosteroid signaling mechanism mediated by the BRI1 receptor kinase. Since joining Carnegie in 2001, his research has illustrated the receptor kinase signaling pathway that links the BRI1 receptor kinase to the BZR1 transcription factor and brassinosteroid-responsive genes in the Arabidopsis genome. He further demonstrated how the steroid signaling pathway integrates at the molecular level with other hormonal pathways, light signaling pathways, nutrient-sensing pathways, immunity pathways, and the circadian clock, to coordinately regulate plant growth and development. His lab uses combinations of genomic and proteomic approaches to understand how cellular signals are transduced and integrated through posttranslational modifications (e.g. phosphorylation and O-Glycosylation) and protein-protein interactions. His studies are elucidating the molecular mechanisms that control plant growth and mediate responses to environmental changes. -
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.
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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.
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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.
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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.
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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
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.
Website: https://nanguage.github.io/ -
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.
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Zehua Zeng
Graduate Visiting Researcher Student, Genetics
BioZehua Zeng is currently a visiting PhD Student at the Qiu lab of Department of Genetics at Stanford. Zehua’s Ph.D. work at University of Science and Technology Beijing with Dr. Hongwu Du and Sun-Yet-sen University with Yuanyan Xiong made critical contributions to the field of multi omics analysis and Agent systems, exemplified by the development of OmicVerse for building one of the largest multi-comics algorithm community.
