Ann B Lee
Professor, Co-Director of the STAMPS@CMU Research Center
Department of Statistics & Data Science / Machine Learning Department, Carnegie Mellon University
About me
I am a professor in the Department of Statistics & Data Science at Carnegie Mellon University, with a joint appointment in the Machine Learning Department. Prior to joining CMU, I was the J.W. Gibbs Assistant Professor in the department of mathematics at Yale University, and before that I served a year as a visiting research associate in the department of applied mathematics at Brown University.
My research interests are in developing statistical methodology for complex data and problems in the physical sciences. I am particularly interested in trust-worthy scientific inference and reliable uncertainty quantification, and in bridging classical statistics and machine learning for simulation-based inference and experimental design. My recent work includes likelihood-free inference, calibrated probabilistic forecasting, interpretable diagnostics of generative models, and applications in astronomy and hurricane intensity guidance involving satellite imagery and large surveys.
I co-founded the STAtistical Methods for Physical Sciences (STAMPS) Research Center at Carnegie Mellon University together with my colleague Mikael Kuusela.
See Google Scholar for my publications and preprints (I’ve been slow at updating my list of selected publications)
Interests
- Scientific Machine Learning
- Trust-Worthy Uncertainty Quantification
- Likelihood-Free Inference
- Statistical Methods for the Physical Sciences
Education
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PhD in Physics
Brown University
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MSc/BSc in Engineering Physics
Chalmers University of Technology, Sweden
