معرفی
Peter Freeman is an Associate Teaching Professor and Director of the Undergraduate Program in the Department of Statistics & Data Science at Carnegie Mellon University's Dietrich College of Humanities and Social Sciences. He holds a B.A. in Physics (1989, University of California) and a Ph.D. in Astronomy and Astrophysics (1997, University of Chicago). Before joining CMU in 2004, he worked as a scientific programmer for the Chandra X-ray Telescope mission, specializing in data analysis methodologies.
His research focuses on astrostatistics, developing advanced statistical techniques for analyzing complex astronomical datasets. Key areas include source detection algorithms, cosmic microwave background mapping, photometric redshift estimation, and galaxy morphology analysis. He has collaborated with faculty and students from CMU and the University of Pittsburgh on interdisciplinary projects, integrating machine learning and computational methods into astrophysical research.
Freeman is actively involved in educational initiatives such as the STAMPS (Statistical Pedagogy & Educational Research) group and the Carnegie Mellon Sports Analytics Camp (CMSAC). His work emphasizes authentic, community-engaged learning experiences, particularly in undergraduate laboratory courses and data science curricula.
His recent publications span astrostatistics, ecological studies (e.g., Coqui frog acoustic analysis), and pedagogical innovations in STEM education. He has contributed to major projects like the Rubin Observatory Legacy Survey of Space and Time (LSST) and the CANDELS galaxy structure classification effort.
