School of Medicine
Showing 341-350 of 364 Results
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Douglas Vollrath
Professor of Genetics and, by courtesy, of Ophthalmology
On Partial Leave from 09/01/2025 To 02/28/2026Current 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 -
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.
