Edward H. Kennedy
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My research interests span 
  • causal inference,
  • high-dimensional data,
  • machine learning, and
  • non- and semi-parametric theory.
I am interested in applications in
  • criminal justice,
  • health services,
  • medicine, and
  • public policy. ​

Biography

Edward Kennedy is an associate professor of Statistics & Data Science at Carnegie Mellon University. He joined the department after graduating with a PhD in biostatistics from the University of Pennsylvania. Edward's methodological 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 research focuses on problems in criminal justice, health services, medicine, and public policy. Edward is a recipient of the NSF CAREER award, the David P. Byar Young Investigator award, and the Thomas Ten Have Award for exceptional research in causal inference.

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