Markov Chain Analysis, Experimental Algorithms, and Pedagogy

Abstract 

Markov chain Monte Carlo algorithms are a class of algorithms used in sampling, estimation, and inference problems. The theoretical study of the mixing times of Markov chains is an active area that goes back decades. In this talk, I discuss my work in three areas: the theoretical analysis of Markov chain mixing times; research with graduate and undergraduate students in experimental algorithms; and neuroinclusive pedagogy. I give an overview of the main ideas in two of my papers, bounding the mixing time of the triangulation flip walk. I then briefly discuss some of my work (in progress) with students, empirically evaluating greedy algorithms in random graphs and Euclidean TSP approximation algorithms. Finally, I discuss my interest in pedagogical research and a survey I am developing to investigate peer support and belonging among neurodiverse students.

Biography

I am a third-year assistant professor at California Polytechnic State University, San Luis Obispo (Cal Poly SLO). At Cal Poly, I teach theory courses and do research in the analysis of algorithms, especially Markov chain Monte Carlo algorithms. I mentor students on experimental aspects of algorithms, helping them to build research skills while strengthening their software engineering, evaluation, and testing skills. I am also developing a line of research on supporting neurodiverse students in computer science education. Before starting at Cal Poly, I did my M.S. and Ph.D. in computer science at the University of California, Irvine (UCI), advised by David Eppstein. My research focused initially on graph theory and computational geometry, with a shift towards Markov chain analysis later during the Ph.D. During graduate school, I worked at Google for three summers, as a software engineering intern and a student researcher. Before graduate school, I did some research at the University of Maryland, College Park. For my undergraduate degree, I studied computer science at Oberlin College in Ohio. I was then a web developer for 11 years before graduate school, having worked for the National Institutes of Health as well as a number of nonprofit organizations.