Stanford University
Showing 34,421-34,440 of 36,231 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. Dr. Wu's current research aims to tackle the pressing issues and challenges in the energy field by utilizing quantum technology. He received his Ph.D. in Electrical Engineering from Stanford University, where he worked with Prof. Yi Cui and collaborating closely with Prof. Harold Y. Hwang. During his doctoral studies, he developed innovative methods to control the properties of two-dimensional materials using guest species, which opened new avenues for their use in quantum and energy applications.
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Yilei Wu
Laboratory Services Manager 2, Chemistry
BioAs a research scientist at Stanford University, I am passionate about advancing the field of organic electronics and solar energy conversion. I have over 15 years of experience in designing, synthesizing, and applying novel organic materials for various applications, such as thin-film transistors, solar cells, spintronics, fluorescence imaging, and molecular machines. I work to develop high-performance organic materials for solution printable solar cells and wearable electronics. I leverage my expertise in supramolecular chemistry, thin-film deposition, and device characterization to optimize the donor-acceptor interfaces and bulk morphology of organic photovoltaic materials. My work contributes to the development of flexible and lightweight solar cells that can provide a sustainable and versatile solution for the modern military and civilian needs.
I oversee the operation and management of Chemistry department laboratory teaching facilities. I also oversee and administer health and safety programs and ensure safety compliance.
As instructor, I teach CHEM 100: Chemical Laboratory and Safety Skills. This is a short in-lab course that is only held in the second week of the Autumn quarter. It provides training in basic chemical laboratory procedures and chemical safety to fulfill the safety training requirement for CHEM 121 and more advanced laboratory courses. The following topics are covered: Reading and Understanding Safety Data Sheets (SDS), Exploring Hazards and Risks, Waste Management, Basic Purification (TLC, Extraction, Filtration, etc.) and Analysis Techniques. In spring 2026 I will teach CHEM 121: Understanding the Natural and Unnatural World through Chemistry. -
Yingcheng Wu
Postdoctoral Scholar, Pathology
BioYingcheng (Charles) Wu is a researcher specializing in Agentic AI for Medicine, advised by Le Cong and Mengdi Wang. Charles has published studies in top-tier journals including Cell, Science, Nature, and Cancer Discovery, and is a recipient of the ICIS Sidney & Joan Pestka Award, the IUBMB Young Scientist Program Fellowship, and the APASL Young Investigator 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.
