Madhav Marathe is a Distinguished Professor in Biocomplexity, the division director of the Network Systems Science and Advanced Computing Division at the Biocomplexity Institute and Initiative, and a Professor in the Department of Computer Science at the University of Virginia (UVA). His research interests are in network science, computational epidemiology, AI, foundations of computing and high performance computing. Over the last 20 years, his division has supported federal and state authorities in their effort to combat epidemics in real-time, including the H1N1 pandemic in 2009, the Ebola outbreak in 2014 and most recently the COVID-19 pandemic. Before joining UVA, he held positions at Virginia Tech and the Los Alamos National Laboratory. He is a Fellow of the IEEE, ACM, SIAM and AAAS.
AI Driven Epidemic Science
COVID-19 pandemic is the most significant pandemic since the 1918 Influenza pandemic. It has had a significant social, economic and health impact globally. I will give an overview of the state of the art in computational epidemiology. I will then describe how data-driven scalable AI and analytics play an important role in supporting policy makers as they respond to the COVID-19 pandemic. I will conclude by articulating the challenges encountered while developing analytical tools as a pandemic is unfolding.