Li Li

VP, Clinical Informatics

Li Li, M.D., is Vice President of Clinical Informatics at Sema4, leading the development of a common data model for electronic medical records (EMR), driving the development and improvement of clinical applications for reproductive diseases, newborn health, and deep imaging learning and aiming to advance novel diagnostics, therapeutics, and insights into both diseases and wellness.

Also, Dr. Li is an Assistant Professor at the Icahn School of Medicine at Mount Sinai in the Department of Genetics and Genomic Sciences and the Institute for Next Generation of Healthcare.

Dr. Li was trained as both a physician and bioinformatician, with an M.D. in Clinical Medicine from the Dalian Medical School in China and an M.S. in Bioinformatics from Boston University, and has over 16 years of experience in both industry (Quest Diagnostics) and academia (Stanford University, UCSD) with a focus on EMR and multi-omics data. At graduate school, she developed RDOCK, which has become one of the most widely-used protein-protein docking software programs. She successfully established the precision medicine groundwork including deep phenotyping of Lyme Disease, categorizing subtypes of type 2 diabetes for treatment stratification rather than one size fits all model, developing deep machine learning algorithms to improve disease prognostics, identifying key clinical risk factors from EMR to improve quality of care for patients, and developing biomarker diagnostic assays for acute rejection and tolerance of kidney transplantation. She has received four Young Investigator Awards from the American Society of Transplantation and the Transplantation Society. Her three international patents led to the creation of the start-up company Organ-I Inc., acquired by IMMUCOR Inc., and one patent of identification of drug targets to treat kidney fibrosis and chronic graft injury. Dr. Li has published extensively in the fields of precision medicine, bioinformatics, and clinical bioinformatics, with more than 75 peer-reviewed papers in journals including Nature Biotechnology, Science Translational Medicine, and PNAS.