Colloquium - Julia Palacios
Institution: Stanford University
Title: Distance-based Summaries and Modeling of Evolutionary Trees
Date: September 27, 2022
Location: Zoom (Click here for meeting details)
Time: 10:20 AM - 11:10 AM Eastern Time
Ranked tree shapes are mathematical objects of great importance used to model hierarchical data and evolutionary processes with applications ranging across many fields including evolutionary biology and infectious disease transmission. While Bayesian methods allow exploration of the posterior distribution of trees, assessing uncertainty and summarizing tree distributions remains challenging for these types of structures. Similarly, in many instances, one seeks to summarize samples of trees obtained with different methods, or from different samples and environments, and wishes to assess stability and generalizability of these summaries. Here, we exploit recently proposed distance metrics of unlabeled ranked evolutionary trees and provide an efficient combinatorial optimization algorithm for estimating Fréchet means and variances. We show the applicability of our summary statistics for studying popular tree distributions and for studying the evolution of viruses.
Dr. Julia A. Palacios is an Assistant Professor in the departments of Statistics, Biomedical Data Science, and Biology (by courtesy) at Stanford University. Professor Palacios completed her PhD in Statistics at the University of Washington in 2013. She did a joint postdoc at Harvard University and Brown University before joining Stanford. In her research, Professor Palacios seeks to provide statistically rigorous answers to concrete, data-driven questions in population genetics, epidemiology, and comparative genomics, often involving probabilistic modeling of evolutionary forces and the development of computationally tractable methods that are applicable to big data problems. She was recently awarded the Alfred Sloan Fellowship, the Stanford Terman Fellowship and the NSF Career award.
Arkaprabha Ganguli, STT PhD candidate, received a 2022 IMS International Conference on Statistics and Data Science student travel award to present his work “Feature selection integrated deep learning for ultrahigh dimensional and highly correlated feature space.” In recognition of this award, his name appeared in the first page of the 2022 October/November issue of the IMS Bulletin https://imstat.org/wp-content/uploads/2022/07/Bulletin51_7.pdf .
Congratulations to PhD candidate Sarah Manski for winning first place for her oral presentation at the 2022 Conference on Applied Statistics in Agriculture and Natural Resources in May at Utah State University in Logan, Utah.
Abhijnan Chattopadhyay graduated from MSU with a Ph.D. in statistics this summer under the co-mentorship of Tapabrata Maiti and David Kramer. As a statistician, Abhijnan had the flexibility and skillset to work in several disciplines, which is how he found himself at the MSU-DOE Plant Research Laboratory (PRL).
PhD candidate Andriana Manousidaki was recently presented with the 2021-2022 William L. Harkness Award for outstanding teaching by a graduate student. The award is made possible by a generous gift from William Harkness, a doctoral alumnus from the Department of Statistics and Probability. Recipients are chosen for their remarkable teaching based on student evaluations and faculty observations of teaching.