I am a grad student in applied math at UCDavis from 2013 to 2020 (expected).
Office: MSB2141. Email: (first name initial + last name full) @ ucdavis.
My CV (updated: Feb 22nd, 2019).
I am broadly interested in information theory and statistics with memory constraints. I am currently studying these in the context of distributed machine learning with James Sharpnack’s. In the past few years, I have become interested in networks and graph algorithms. My work involves a blend of theory and computation.
- [Fall 2019] I am a TA for MAT12 Pre-Calculus with Korana Burke.
Recent academic work
- [Fall 2019] James presented our work on scan statistics epidemiology at GeoVet 2019. I am thinking about hierarchical compressed communication again.
- [Summer 2019] I am working on a project to apply scan statistics to epidemiology with Beatriz Lopez and James Sharpnack.
- [Spring 2019] Our paper “Estimating Graphlet Statistics via Lifting” was accepted for a poster presentation at KDD2019! Big thanks to Kiril Paramonov for the conceptual work and to James for including me on the project.
- [Fall - Winter 2019] I organized the math/stats reading group “Information Theory and Statistics”.
- [July 2018] I gave a talk on “Statistical Limits in Hierarchical Communication” in the Student Chapter Presentations section at the 2018 SIAM Annual Meeting in Portland, Oregon.
- [June 2018] I passed my qualifying exam! I defended a project proposal titled “Towards Statistical Limits in Hierarchical Communication”.
- [Summer 2017] I worked at Los Alamos National Lab with Marc Vuffray and Andrey Lokhov on parameter learning in models of power transmission. Our project paper was accepted for presentation at PSCC2018: “Online Learning of Power Transmission Dynamics”, [Arxiv], [IEEE].
- [Summer 2014 - Winter 2016] I studied the inference of stochastic processes with memory, modeled by Hidden Markov Models, using information theory and computational mechanics. Kelly Finn and I analyzed times series data of moving monkeys using various measures of complexity such as entropy rate, statistical complexity, and excess entropy. I was supervised by Jim Crutchfield.