Edward Kennedy, an associate professor in Carnegie Mellon’s Department of Statistics & Data Science, received the Mortimer Spiegelman Award for his outstanding contributions to public health and statistics. Kennedy joined Carnegie Mellon University after graduating with a PhD in biostatistics from the University of Pennsylvania. Edward’s research interests lie at the intersection of causal inference, machine learning, and nonparametric theory, especially in settings involving high-dimensional and otherwise complex data. His applied work focuses on problems in criminal justice, health services, medicine, and public policy. Edward is a recipient of an NSF CAREER Award, and the 2015 Thomas Ten Have Award for exceptional research in causal inference. Read more at https://www.cmu.edu/dietrich/news/news-stories/2024/september/spiegelman-kennedy.html