معرفی
Persi Diaconis is the Mary V. Sunseri Professor of Statistics and Professor of Mathematics at Stanford University, with a joint appointment in the Symbolic Systems Program. He has held these positions since 1998 and previously served as a professor at Harvard University and Cornell University. His work bridges mathematics and statistics with applications across scientific computing and data analysis.
Diaconis is renowned for his research in probability theory, combinatorics, and group theory, with a specialty in rates of convergence of Markov chains. His current research focuses on adapting mathematical developments to practical applications in large real-world simulations. He has opened up new areas in Markov chain theory including rates of convergence to quasi-stationarity and the study of "features" in chains. His work extends to statistical analysis of graph and network data, generalizations of de Finetti's notion of exchangeability, and connections between statistics and graph limit theory.
An analysis of his recent publications reveals a strong focus on Markov chain theory, combinatorial probability, and statistical applications. His work demonstrates interdisciplinary connections between pure mathematics, theoretical statistics, and practical computing problems. Diaconis frequently collaborates with researchers like Sourav Chatterjee, Susan Holmes, and Jason Fulman on problems ranging from card shuffling to network analysis.
- Honorary doctorate from University of St Andrews
- Mary V. Sunseri Professorship at Stanford University
- Fellow of the Center for Advanced Study in the Behavioral Sciences (1999-2000)
Diaconis has advised numerous doctoral students including Michael Howes, Zhiqi Li, Andrew Lin, and Nathan Tung. His research has been supported by various grants that enable his work on Markov chains, combinatorial probability, and statistical theory. He has developed important connections between theoretical mathematics and practical statistical applications, influencing both academic research and real-world problem solving.
While not explicitly mentioned as leading a specific lab, Diaconis collaborates extensively with researchers across Stanford and globally. His work with the Symbolic Systems Program connects mathematics with cognitive science and computer science. His research group focuses on probabilistic and combinatorial problems with applications to data science and scientific computing.
