Chad Schafer is a Professor in the Department of Statistics & Data Science at Carnegie Mellon University (CMU), affiliated with the Dietrich College of Humanities and Social Sciences. He holds a Ph.D. in Statistics from UC Berkeley (2004), an M.S. from the University of Illinois at Urbana-Champaign, and a B.S. from Western Michigan University. Prior to academia, he contributed to climate modeling at Argonne National Laboratory. His research focuses on astrostatistics, addressing complex data structures in cosmology and astronomical surveys like the Sloan Digital Sky Survey (SDSS) and Large Synoptic Survey Telescope (LSST). Key areas include statistical inference in high-dimensional settings, nonparametric methods, and computational frameworks for large-scale scientific data. He emphasizes collaboration with domain scientists through CMU's McWilliams Center for Cosmology. Publications highlight advancements in galaxy density analysis, machine learning applications, and software frameworks (e.g., LINCC, KBMOD) for astrophysical data. Schafer also advocates for interdisciplinary education, emphasizing technical skills and software sustainability in astronomy. His work bridges statistical theory with real-world challenges in modern astrophysics.





