Assistant Professor Michael J. Paul develops methods for analyzing and understanding data. His background is in machine learning, statistical modeling and natural language processing, which he uses to solve problems in health informatics and epidemiology, using new and transformative sources of data. For example, his research has shown how to analyze social media to monitor disease outbreaks and track trends in population health.
Paul received a PhD in Computer Science from Johns Hopkins University in 2015 and a BS in computer science from the University of Illinois at Urbana-Champaign. He was awarded graduate fellowships from Microsoft Research and the National Science Foundation and has interned at Twitter and Microsoft Research. His research has been featured in The Washington Post, CNN and NPR.