Stanford University
Showing 1,851-1,860 of 13,070 Results
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Richard Owguan Chen, MD
Clinical Assistant Professor, Dermatology
BioRichard Chen, M.D. M.S., is Clinical Assistant Professor of Dermatology at Stanford and Chief Scientific Officer at Personalis, Inc. He attended medical school and completed residency at Stanford University, serving as Chief Resident in his final year. His interests include general dermatology, cancer genomics, precision medicine, genetics, bioinformatics and technology innovation for improved health care delivery and therapy.
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Sharon F. Chen
Clinical Professor, Pediatrics - Infectious Diseases
Current Research and Scholarly InterestsMy interest is in viral infections affecting immunocompromised patients. As Co-director of Stanford Childrens' PIDPIC, I develop and conduct clinical studies to establish best practices and start new clinical initiatives that push the frontier.
My scholarly interests also extends to education research in how people think and make decisions. I am building an AI tool that humans can use as a partner to improve their critical thinking and problem-solving skills. -
Sijie Chen
Postdoctoral Scholar, Radiation Physics
BioI am a postdoctoral fellow working with Dr. Lei Xing at Stanford University, where I develop trustworthy autonomous AI agents and foundational informatics systems for single-cell biology. My long-term vision is to build auditable computational infrastructure and virtual cell models that transform massive single-cell atlases into reliable, steerable systems for mechanistic discovery across tissues, diseases, and species. My doctoral work with Prof. Xuegong Zhang established my foundation in single-cell bioinformatics and atlas-scale integration, which I have since extended into large-scale representation modeling, AI agent workflows, and LLM-driven scientific discovery. My current work focuses on developing governed, agentic lifecycles for continuous single-cell data curation and foundation model evaluation, while applying these autonomous systems to power cross-organ virtual cell retrieval and simulate immune-tolerance breakdown.
My ongoing efforts build directly upon my prior work in atlas integration and algorithmic development. As the first author of hECA (Chen et al., 2022), I built a unified human cell atlas integrating one million high-quality cells across 38 organs with a logic-expression query interface. This experience exposed the central bottlenecks—such as heterogeneous formats and ontology grounding—that I now address using LLM-powered agents to enable autonomous metadata harmonization and iterative quality control. I am converting manual curation into an autonomous, agent-driven paradigm where new datasets are continuously ingested and versioned in a traceable manner. Furthermore, my co-development of TorchGW for cell state alignment, TFcomb for perturbation prediction, and TransMap for cross-species alignment provides the algorithmic foundation for next-generation cell foundation models and virtual cell simulation.
By integrating these components into trustworthy, benchmarked, and human-in-the-loop AI infrastructure, my research bridges scalable scientific computing with complex biomedical questions. Through close collaboration with Prof. Edgar Engleman, I am utilizing immune-tolerance breakdown—specifically focusing on a tolerogenic dendritic cell program—as a mechanistic testbed to validate our virtual cell simulations. A core focus of my work is ensuring that every agent-generated hypothesis and retrieved state remains bound to the exact data and model checkpoints that produced it, making findings fully re-derivable as the biological knowledge base evolves. Ultimately, I aim to advance the frontier of trustworthy autonomous single-cell informatics, bridging AI agents, virtual cell engineering, and biological discovery. -
Tianqi Chen
Postdoctoral Scholar, Oncology
BioMy research interest lies in liquid biopsy and early cancer diagnostics, e.g. development of bioassay for detection of cancer biomarkers (proteins and genes) and single-cell research. As well as the integration of 3D-printed microfluidics.
