I am a professor and chair of the Department of Statistics at Carnegie Mellon University. After earning a Ph.D. in statistics at the University of California, Berkeley, in 1994, I came to Carnegie Mellon. My research focuses on high-dimensional and nonparametric inference problems, especially related to complex scientific questions. My applied work covers a range of scientific areas, including cosmology, neuroscience, and evolutionary biology. I am leading a project to develop a system for inferring students learning state (at a skill-by-skill level) from rich on-line learning data. A more recent project with researchers at Magee-Womens Hospital will develop novel methods for predicting placental and fetal health from trace signals measured during pregnancy.
My research interests center around making effective inferences in complex scientific problems. On the applications side, I have active collaborations in neuroscience, cosmology, astronomy, and entomology. On the theoretical side, I am interested confidence sets for nonparametric inference, adaptive function estimation, spatial statistics, inverse problems, and multiple testing.