Lecture 1 Thursday, May 31, 2012

We are pleased to have Professor S. R. S. Varadhan, of the Courant Institute of Mathematical Sciences at New York University, as our honored speaker.

Thursday, May 31, 2012, at 4:00 PM
Eckhart 133, 5734 South University Avenue
Reception following the lecture in Eckhart 209.

"Large Deviations with Applications to Random Matrices and Random Graphs"

Scenes from the lecture

Introduction to the First Billingsley Lecture on Probability Theory

Welcome to the first Billingsley Lecture on Probability Theory. This is the first in what will be an annual series of special lectures to commemorate the contributions of Patrick Billingsley to the field of probability theory and to the University of Chicago, where Pat spent nearly all of his academic career, from 1958 until his retirement in 1994.

Pat Billingsley was a man of diverse talents: he excelled not only as a scholar and a teacher but also as a writer, an actor, and even a black belt in judo. Pat is remembered for his research in weak convergence, in ergodic theory and its connections with information theory, in probabilistic number theory, and as the inventor of the "Billingsley dimension" of a measure. He advised a number of Ph.D. students during his years on the UC faculty, several of whom went on to distinguished careers in mathematics, including Rabi Bhattacharya and Richard Gundy. He played leading roles in more than 20 productions of the Court Theater, and also appeared in a number of movies and television shows. Pat once remarked to me that he suspected he was one of the few people alive whose Erdös number and his Kevin Bacon number summed to less than ten. (He did not know of Wendelin Werner another distinguished probabilist who like Pat has an Erdös-Bacon number of 6. In fact, Pat shares 12th place in this category, along with Werner, Richard Feynman, John Nash, and Tom Lehrer.)

But what we in the fields of probability and statistics mainly remember Pat for are his superb monographs and textbooks on weak convergence, ergodic theory and information, inference for Markov chains, and the measure-theoretic foundations of probability. These books are all models of mathematical exposition, and "Probability and Measure" remains a widely used and frequently cited graduate textbook. A generation of probabilists and statisticians in the United States learned about the measure-theoretic underpinnings of probability from this book.

Pat would have been pleased to be honored by a lecture series such as this, and especially proud that the first lecture would be delivered by Raghu Varadhan.