Matthew MightView profile
Professor
Matthew Might is a Professor of Internal Medicine and Computer Science at the University of Alabama at Birmingham's Heersink School of Medicine, where he serves as Director of the Hugh Kaul Precision Medicine Institute and Co-Director of the Center for Precision Animal Modeling. He also holds a position as Senior Lecturer in the Department of Biomedical Informatics at Harvard Medical School. His career spans academia, government service at The White House (2016-2018), and industry as co-founder of Pairnomix, LLC and Q State Biosciences, Inc. Might's research program uniquely bridges computer science and precision medicine, born from his personal quest to diagnose his son Bertrand who was the first identified case of a novel genetic disorder. His work applies data science, artificial intelligence, machine learning, and formal reasoning to accelerate biomedical science in service of patients. His broader interests include oligonucleotide therapeutics, model organisms, drug screening, and medicinal chemistry. As Director of the Precision Medicine Institute, he oversees a comprehensive research portfolio that includes significant bench science targeted at tailoring therapeutics to individual patients. Analysis of Might's recent publications reveals a strong focus on rare genetic disorders, particularly NGLY1 deficiency, with extensive work on disease modeling using induced pluripotent stem cells (iPSCs). His research spans multiple disciplines including genomics, proteomics, neurology, and drug discovery, with a notable emphasis on the Undiagnosed Diseases Network. Recent work has also addressed the COVID-19 pandemic through computational drug discovery and investigations into viral pathogenesis. Throughout his career, Might has maintained a dual focus on theoretical computer science and practical medical applications. His early work included significant contributions to programming language theory, abstract interpretation, and control-flow analysis, which he has successfully translated into biomedical applications. He has been instrumental in developing computational approaches to rare disease diagnosis and matchmaking patients with similar conditions. Might has been actively involved with the Undiagnosed Diseases Network, contributing to numerous collaborative studies that have advanced understanding of rare genetic conditions. His work emphasizes patient-centered approaches to precision medicine, with projects focused on genomic healthcare empowerment and family communication of genetic results. He has also developed innovative computational methods for RNA-seq analysis and drug screening. His leadership extends to directing research teams working on multiple fronts of precision medicine, including laboratory-based investigations of genetic disorders, computational approaches to drug discovery, and patient matchmaking strategies for rare disease communities. Might's interdisciplinary approach has created bridges between computer science theory and practical clinical applications, demonstrating how computational methods can directly impact patient care for those with rare and undiagnosed conditions.
