معرفی
Thomas Severini is a Professor of Statistics and Data Science at Northwestern University's Weinberg College of Arts & Sciences. He holds a Ph.D. from the University of Chicago (1987). His research focuses on likelihood-based statistical methods, including higher-order asymptotic approximations and applications in finance, econometrics, and sports analytics. He has authored influential works such as Introduction to Statistical Methods for Financial Models (2017) and Analytic Methods in Sports (2014).
Key research interests include: (1) Development of statistical methodology for complex models, (2) Application of likelihood-based techniques in finance/econometrics, (3) Analysis of sports performance data. Notable contributions include work on integrated likelihood functions and jet lag effects on MLB performance.
Publications span top journals like Biometrika, Journal of Econometrics, and Proceedings of the National Academy of Sciences. His work bridges theoretical statistics with practical applications in diverse domains.
