1. Jun Liu
Professor
Tsinghua university
Title: TBA
Abstract: TBA
Bio: TBA
2. Marc Suchard
Professor
University of California Los Angeles
Title: Simple approximations for scalable Bayesian computing in phylogenetics
Abstract: Bayesian computation remains onerous at scale for inference under many discrete-valued stochastic process-based models, while these statistical models remain ubiquitous across biology and public health. In this talk, I will explore how one can construct reliable approximations for continuous-time Markov chain (CTMC) models. CTMCs underpin the most popular models for learning about how rapidly evolving pathogens change over time and space to give rise to human infection, and the dimensionality of these problems are daunting. These approximations enable the introduction of novel random-effects and non-parameteric CTMC models that capture biological realism previously missing. Applied to the analysis of yellow fever and Ebola viruses, these models remove bias in inference of the factors driving transmission, while the statistical machinery is over an order of magnitude more time efficient than conventional approaches.
Bio: Dr. Suchard is Professor in the Departments of Biostatistics and of Computational Medicine at the University of California, Los Angeles (UCLA). His research focuses on large-scale inference of stochastic processes in genomics and observational healthcare. He received his BA in biophyics from the University of California, Berkeley and MD and PhD in biomathematics from UCLA. He has authored over 350 peer-reviewed publications, is the 2003 recipient of the Savage Award, an international prize for the best Bayesian dissertation, received the 2006 and 2011 Mitchell Prizes, the premier award in applied Bayesian statistics, a 2008 Guggenheim Fellowship to promote Bayesian approaches in medicine and Research Gifts from Microsoft Corporation and Google to further statistical computing. He is also the recipient of the 2013 Committee of Presidents of Statistical Societies (COPSS) Presidents’ Award for outstanding contributions to the statistics profession by a person aged 40 or under and the 2021 Jerome Sacks Award for Outstanding Cross-Disciplinary Research. He holds fellowships in the American Statistical Association, the Institute of Mathematical Statistics and the International Society for Bayesian Analysis.
