Associate Professor, Department of Statistics, Carnegie Mellon University


My primary objective is the development of statistical methods for addressing important questions in the sciences, primarily astronomy. This focus dates back to my Ph.D., working with Philip Stark in the Department of Statistics at UC Berkeley.

One specific, recurring theme in my research is the rigorous handling of the complex models and data structures that increasingly dominate the sciences. For example, cosmological models are characterized by key unknown physical constants; modern astronomical surveys generate data that hold great promise to accurately estimate these quantities, but this requires statistical methods that are tailored to the theoretical models and noisy, high-dimensional data that abound in the field.

I enjoy maintaining close interaction with the domain scientists, and have benefited significantly from the McWilliams Center for Cosmology at CMU and its strong links to the Sloan Digital Sky Survey (SDSS) and the Large Synoptic Survey Telescope (LSST), two of the largest data-gathering endeavors in astronomy. I currently serve as the co-chair (with Tom Loredo) of the LSST Informatics and Statistics Science Collaboration.

I place great emphasis on teaching and other educational activities. I have taught a wide range of courses while at CMU, from introductory-level undergraduate statistics to measure-theoretic probability. I currently serve on the Steering Committee for CMU's Master of Science in Computational Finance (MSCF) Program. Each summer since 2012 I have advised summer research projects for undergraduates, and from 2015 to 2018 I directed our Department's Summer Undergraduate Research Experience program.

Prior to my time at Berkeley, I earned an M.S. in Statistics from the Department of Statistics at the University of Illinois at Urbana-Champaign and a B.S. from Western Michigan University. In between, I spent 1.5 years working at the Mathematics and Computer Science Division of Argonne National Laboratory, helping to construct a climate model.