Sébastien Roch is a Professor of Mathematics at the University of Wisconsin–Madison, where he is also affiliated with the Department of Statistics and the Theory of Computing Group. He earned his PhD in Statistics from the University of California, Berkeley. He is the recipient of an NSF CAREER Award, an Alfred P. Sloan Fellowship and a Simons Fellowship. He also received the Best Paper Award at RECOMB 2018. In 2022, he was named Fellow of the IMS. His graduate textbook, Modern Discrete Probability: An Essential Toolkit, was recently published. This IMS Medallion Lecture will be given at the Seminar on Stochastic Processes (SSP) 2024 meeting (March 13–16, 2024, at Rice University in Houston, USA: see https://ssp2024.rice.edu/home).

Complex Probabilistic Models in Evolutionary Biology: Challenges and Opportunities

The reconstruction of species phylogenies from genomic data is a key step in modern evolutionary studies. This task is complicated by the fact that genes evolve under biological phenomena that produce discordant histories. These include horizontal gene transfer, gene duplication and loss, and incomplete lineage sorting, all of which can be modeled using random gene tree distributions building on well-studied stochastic processes (branching processes, the coalescent, etc.). Gene trees are in turn estimated from molecular sequences using Markov models on trees. The rigorous analysis of the resulting complex models can help guide the design of new reconstruction methods with statistical and computational guarantees. I will illustrate the challenges and opportunities in this area via a few recent results. No biology background will be assumed.