School of Medicine
Showing 161-180 of 395 Results
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Alexander Ioannidis
Assistant Professor (Research) of Genetics and of Biomedical Data Science
Adjunct Professor, Institute for Computational and Mathematical Engineering (ICME)BioDr. Ioannidis earned his Ph.D. from Stanford University in Computational and Mathematical Engineering together with an M.S. in Management Science and Engineering (Optimization). He graduated summa cum laude from Harvard University in Chemistry and Physics and earned an M.Phil at the University of Cambridge from the Department of Applied Math and Theoretical Physics in Computational Biology. His research focuses on the design of algorithms and application of computational methods for problems in precision health, genomics, clinical data science, and AI in healthcare.
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Livnat Jerby
Assistant Professor of Genetics
Current Research and Scholarly InterestsCombining and advancing functional genomics, cell engineering, synthetic biology, AI, and basic immunology to uncover, decode, rewire, and develop mechanisms to selectively eliminate and reprogram disease-driving cells as a foundation for disease treatment and prevention.
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Feng Jiang
Postdoctoral Scholar, Genetics
BioI am a postdoctoral researcher working on RNA editing.
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Peter William Earl Kane
Affiliate, Genetics
BioHelping oncology and rare disease patients.
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Amarnath K R
Affiliate, Genetics
BioAmarnath K R is a computational scientist and deep learning engineer driving breakthroughs in biomedical AI specializing in the fusion of multi-omics data, deep learning, and clinical statistics to tackle some of medicine’s most complex challenges. His current work at Stanford University's Department of Genetics focuses on developing a deep learning framework for cross-modal cell type label transfer by aligning single-cell RNA-seq and proteomics data in a shared latent space. Using autoencoders and a joint contrasitive-based training, he achieves highly reliable annotation of unlabeled proteomics cells with RNA-derived ground truth. This work enables accurate integration of transcriptomic and proteomic modalities for downstream biological discovery and holds promise for expanding cell atlases.
What sets Amarnath apart is his commitment to both technical excellence and translational impact. From designing novel transformer architectures for histopathology and image inpainting, to developing AI-powered tools for emergency departments in India, his work is grounded in real-world deployment and global health relevance. His projects span continents and disciplines like, from integrating multi-omics datasets to uncover disease mechanisms and predict therapeutic response, to an acoustic classifier for biodiversity, to decoding brain function through neuroinformatics.
With multiple publications, international collaborations, and an unwavering drive to innovate, he represents a new generation of computational scientists shaping the future of personalized, data-driven medicine. -
Maya M. Kasowski
Assistant Professor of Pathology, of Medicine (Pulmonary, Allergy and Critical Care Medicine) and, by courtesy, of Genetics
BioI am a clinical pathologist and assistant professor in the Departments of Medicine, Pathology, and Genetics (by courtesy) at Stanford. I completed my MD-PhD training at Yale University and my residency training and a post-doctoral fellowship in the Department of Genetics at Stanford University. My experiences as a clinical pathologist and genome scientist have made me passionate about applying cutting-edge technologies to primary patient specimens in order to characterize disease pathologies at the molecular level. The core focus of my lab is to study the mechanisms by which genetic variants influence the risk of disease through effects on intermediate molecular phenotypes.
