معرفی
Alex Reinhart is an Associate Teaching Professor in the Department of Statistics & Data Science at Carnegie Mellon University, affiliated with the Dietrich College of Humanities and Social Sciences. He holds a Ph.D. from CMU and a BS in Physics from the University of Texas at Austin. His research focuses on statistical pedagogy, natural language processing, and applications of spatio-temporal data analysis to crime prediction and radiation detection.
Reinhart’s work emphasizes improving statistical education through innovative methods like writing in the age of AI and psychology case studies. He also explores the intersection of large language models and human-like text generation. His contributions include the book Statistics Done Wrong, which critiques common statistical errors in scientific research.
His recent publications address pandemic-related challenges, such as vaccine hesitancy and real-time data analysis through surveys like the US COVID-19 Trends and Impact Survey. His research spans statistical software development (e.g., the pseudobibeR package) and interdisciplinary applications in public health, biomechanics, and education.
