School of Medicine
Showing 761-770 of 947 Results
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Kyle Loh
Associate Professor of Developmental Biology (Stem Cell)
BioHow the richly varied cell-types in the human body arise from one embryonic cell is a marvel and mystery. We have mapped how human embryonic stem cells develop into over twenty different types of cells. This roadmap allowed us to generate enriched populations of human brain, blood, blood vessel, bone, and other cells in a Petri dish from embryonic stem cells, with implications for developmental biology, stem cell biology, and regenerative medicine. Additionally, we have an emerging interest in exploring deadly biosafety level 4 viruses together with our collaborators.
Kyle attended the County College of Morris and Rutgers, and received his Ph.D. from Stanford (working with Irving Weissman), with fellowships from the Hertz Foundation, National Science Foundation and Davidson Institute for Talent Development. He then continued as a Siebel Investigator, and later, as an faculty member at Stanford. Kyle is a Packard Fellow, Pew Scholar, Human Frontier Science Program Young Investigator and Baxter Foundation Faculty Scholar. His research has been recognized by the NIH Director's Early Independence Award, ISSCR Early Career Impact Award, Forbes 30 Under 30, Harold Weintraub Graduate Award, Hertz Foundation Thesis Prize and A*STAR Investigatorship. -
Quentin Loisel
Postdoctoral Scholar, SCRDP/ Heart Disease Prevention
BioQuentin Loisel is a postdoctoral researcher at the Meta-Research Innovation Center at Stanford (METRICS), where his work focuses on how artificial intelligence is transforming scientific practice and how researchers can use AI to produce better, more robust, and more equitable science. His broader agenda is to help define a hybrid model of scientific inquiry that deliberately and transparently combines human judgment and artificial intelligence.
His research sits at the intersection of artificial intelligence, epistemology of science, and research systems. He studies how AI tools reshape knowledge production across the research lifecycle, from problem formulation and data analysis to writing, peer review, and governance, and examines the epistemic, methodological, and institutional consequences of human–AI collaboration in science. His work aims to move beyond risk-focused or purely technical perspectives by developing evidence-based, researcher-centric models for integrating AI into everyday scientific practice.
Before joining Stanford, he completed a Marie Skłodowska-Curie PhD on digital technologies for co-creation, combining cognitive science, collective intelligence, and participatory research. He has co-funded and is coordinating the Artificial Intelligence working group of the Marie Curie Alumni Association (MCAA), which is a researcher-driven community of practice on AI in research. He also advises a social company, called Health Cascade, on how to integrate AI in teams to solve complex societal problems.
