Stanford University
Showing 32,751-32,760 of 34,514 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 -
Yecun Wu
Postdoctoral Scholar, Physics
BioDr. Yecun Wu is a postdoctoral scholar in the physics department at Stanford University, working with Prof. Steven Chu. His research interests encompass a range of interdisciplinary fields, including quantum sensing, quantum materials, energy storage, and sustainability.
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Yilei Wu
Laboratory Services Manager 2, Chemistry
BioResearch Scientist & Chemistry Teaching Lab Manager, Stanford University
Yilei Wu is a research scientist at Stanford University whose work focuses on advancing organic electronics and solar‑energy conversion. With more than 15 years of experience in molecular design, organic synthesis, and device engineering, his research spans thin‑film transistors, organic photovoltaics, spintronics, fluorescence imaging, and molecular machines. He specializes in developing high‑performance organic materials for solution‑printable solar cells and wearable electronics, integrating supramolecular chemistry, thin‑film deposition, and device characterization to optimize donor–acceptor interfaces and bulk morphology. His work supports the development of flexible, lightweight solar technologies for both civilian and modern defense applications.
In addition to his research, Wu oversees the operation and management of Stanford’s Chemistry teaching laboratories, directing laboratory infrastructure, instructional support, and departmental health and safety programs.
He teaches CHEM 100: Chemical Laboratory and Safety Skills, an intensive in‑lab course that provides foundational training in chemical safety, laboratory techniques, and hazard assessment. He also teaches CHEM 121: Understanding the Natural and Unnatural World through Chemistry, a course that explores how fundamental chemical principles drive innovation across biology, pharmaceuticals, agrochemicals, engineering, energy, and materials science. -
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.
