School of Medicine
Showing 12,571-12,580 of 13,182 Results
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Allen Wu
Principal Engineer At Eli Lilly And Company, Medicine - Med/Cardiovascular Medicine
BioAllen Wu is a machine learning engineer and researcher specializing in large-scale AI/ML infrastructure for biomedical and pharmaceutical applications. He contributed to the development of TuneLab, an Eli Lilly AI/ML platform supporting federated drug discovery with external biotech partners, and Model Gateway, an MLOps inference platform for internal model-driven drug discovery, during his tenure at Eli Lilly. He holds dual MS degrees in Computer Science (National Chiao Tung University, Taiwan) and Software Engineering (San José State University), with publications in both VLSI/EDA and Pharma AI, and is an IEEE peer reviewer and NSTC LEAP Fellow (hosted at Synopsys). His current research interests focus on the intersection of iPSC biology and AI/ML pipelines for precision medicine.
LinkedIn Profile: https://www.linkedin.com/in/yswu123
Google Scholar Profile: https://scholar.google.com/citations?user=ymttL5gAAAAJ -
Yingcheng Wu
Postdoctoral Scholar, Pathology
BioYingcheng (Charles) Wu is an AI4S postdoc advised by Le Cong and Mengdi Wang, focusing on physical AI scientists, biomedical world models, and autonomous science infra. His work combines embodied AI, world model, and agents to build self-driving laboratories. He has published studies in **Cell**, **Science**, **Nature**, and received honors including the ICIS Sidney & Joan Pestka Award, the IUBMB Young Scientist Fellowship, the APASL Young Investigator Award, World’s Top 2% Scientists by Stanford, WAIC Rising Star Award.
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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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Ziyan Wu
Postdoctoral Scholar, Otolaryngology - Head & Neck Surgery
BioZiyan’s PhD research centers around contaminant sensing in the environment using Raman spectroscopy, membrane sensors, and machine learning. At Stanford, Ziyan will continue her research on investigating the health impacts of emerging contaminants.
