I am a Ph.D. candidate in the Department of Statistics and Data Science at Carnegie Mellon University and previously completed an M.S. in machine learning at CMU. My research interests largely lie in the intersection of statistics, machine learning, and cosmology. In particular, my recent work has focused on mapping the large-scale structure of the Universe in three dimensions. On a more theoretical level, my interests span various aspects of supervised learning and spatio-temporal models. I am fortunate enough to have three fantastic advisors in Larry Wasserman, Jessi Cisewski, and Rupert Croft. Before CMU, I received a B.S. in mathematics from the University of Kansas.
In my free time I enjoy endurance sports, reading, traveling, Chipotle burritos, and my dogs, Seth and Max.