I am a Ph.D. candidate in the Department of Statistics & Data Science and Machine Learning Department at Carnegie Mellon University, and also affiliated with the McWilliams Center for Cosmology. The area of research I am most passionate about is the intersection of statistics, machine learning, and cosmology. Much of my Ph.D. work has focused on optimally inverting the silhouettes of the intergalactic medium in the spectra of high redshift quasars to reconstruct one, two, and three-dimensional maps of the Universe's large-scale structure. On a more theoretical level, my interests span various aspects of supervised learning, spatio-temporal modeling, and uncertainty quantification. I am fortunate enough to have three fantastic advisors in Larry Wasserman, Jessi Cisewski-Kehe, and Rupert Croft. I have previously received an M.S. in machine learning from CMU and a B.S. in mathematics from the University of Kansas.In my free time I enjoy athletics, reading, traveling, any food wrapped in a tortilla, and my dogs -- Seth and Max. I changed my last name from Eubanks to Politsch in March of 2019 to honor my late mother.
08/2019 - New paper on arXiv: L1 Trend Filtering: A Modern Statistical Tool for Astronomical Spectroscopy and Time-Domain Astronomy
10/2018 - Three of my classmates and I took 2nd place in The Data Open at CMU hosted by Citadel and Correlation One (300+ applications, ~100 selected to compete).
07/2018 - I will be speaking about my work on constructing the largest 3D map of the Universe to date at JSM 2018 in Vancouver. Abstract
05/2018 - I will be interning as a data scientist at Uber HQ in San Francisco during the summer of 2018
09/2017 - Three of my classmates and I took 2nd place in the 2017 NBA Hackathon (900+ applications, ~200 selected to compete). Recap
09/2017 - Three of my classmates and I took 2nd place in The Data Open at CMU hosted by Citadel and Correlation One (550+ applications, ~100 selected to compete).