School of Medicine
Showing 821-840 of 863 Results
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Xiaojing Xing
Masters Student in Clinical Informatics Management, admitted Summer 2025
BioXiaojing Xing is a health tech founder and product leader working at the intersection of medicine, business, and technology. She has driven AI-powered innovations across hardware and software—building from MVP to scale at both startups and global tech companies.
At Tencent, she led digital health platforms serving over 30 million users and launched AI tools that empowered 200,000+ physicians. Later, as Chief Product Officer at MindLax, she brought a neurofeedback sleep device from concept to market, growing it to thousands of users through data-driven iteration and user empathy.
Recognized on Forbes 30 Under 30 China, Xiaojing blends product management, global go-to-market strategy, and health innovation expertise. She is currently focused on applying AI to consumer health—creating intelligent, accessible technologies that make wellbeing part of everyday life.
Xiaojing holds degrees from Stanford University School of Medicine, Harvard T.H. Chan School of Public Health, and Peking University Health Science Center. -
Johnny (Yue) Yang
Ph.D. Student in Biomedical Physics, admitted Autumn 2026
BioJohnny (Yue) Yang's research focuses on Computer-Assisted Intervention, Human-Computer Interaction, and Extended Reality (XR). He is actively researching empowering technologies like Augmented Reality and Surgical Robots to help surgeons perform surgery. Before joining Stanford, he graduated from Johns Hopkins University with a double major in Applied Mathematics and Public Health Studies. He has published in venues like CHI, IEEE-TVCG, etc.
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Christine Yiwen Yeh
MD Student, expected graduation Spring 2027
Ph.D. Student in Biomedical Data Science, admitted Autumn 2020
MSTP StudentBioChristine Yeh is an aspiring physician-scientist with academic training and industry experience in translational bioinformatics and data science. Christine is currently a sixth year MD/PhD candidate in the Medical Scientist Training Program (MSTP) at Stanford. She is interested in advancing cancer care through the integration of clinical oncology, computational cancer biology, and translational research, with the goal of developing more precise and effective therapies. In June 2025, she completed her PhD in Biomedical Data Science. In her doctoral work she developed a novel unsupervised machine learning pipeline grounded in principles of algorithmic fairness and applied it to single-cell spatial transcriptomics and CRISPR-based functional genomics to identify mechanisms of immune evasion and therapeutic vulnerabilities in tubo-ovarian cancer. Prior to MD/PhD training, Christine was a computational structural biologist and drug discovery scientist at D. E. Shaw Research in New York City. There, she built machine learning algorithms for investigating protein structural dynamics and worked on several early drug discovery programs for diabetes and immuno-oncology indications. Christine’s drug target panel included non-receptor protein tyrosine phosphatases encoded by PTPN1 and PTPN11. Her work led to peer-reviewed publications describing lead compounds and a novel small molecule therapeutic that advanced to and completed early phase clinical trials.
