Our university is unique in combining strength in AI spearheaded by Columbia Engineering with a top-flight medical campus within the same institution. The AI research done within SEAS thus develops tools and methodologies across biomedicine, from basic-science biology all the way to patient-facing apps. As exabytes of health-relevant data flood biomedicine, from DNA sequences of people, microbes and engineered biotechnological gadgets, through multi-channel imaging across scales, to texts of electronic health records and patients’ social media posts, projects and labs use machine learning applied to such Big Data to advance understanding of biological systems at all levels: from the folding and binding of single molecules that is critical for drug design, through the dynamics of bacterial communities within our bodies, to the landscape of single cells interacting in healthy and diseased tissues. This impacts applications in medicine across our sister schools of Nursing, Dentistry, Public Health, and Medicine spanning many diseases: autism and schizophrenia, Alzheimer’s and Parkinson’s, diabetes and hypertension, cancers and infectious diseases just to name a few. It also leads to opportunities of collaborations with the Zuckerman Mind Brain Behavior Institute in understanding or treating neurological diseases or functional degradations. Intelligent systems we develop interact with the healthy population to promote wellness by tracking exercise patterns and their impact, providing individualized, data derived nutritional advice, and teasing apart the kaleidoscopic genetic diversity within our metropolitan area and beyond.
