Academic History

I earned a PhD in Applied Mathematics from University of California, Davis in 2021, advised by James Sharpnack. My Google Scholar has my publications.

My PhD work studied statistical problems on graphs. Specifically, I was interested in

• information theory and statistics with memory constraints,
• networks and graph algorithms,
• combinatorics, probability, and Markov Chains.

Timeline

• Mar, 2021 Finished my dissertation titled “Concerning Some Statistical Problems on Graphs” and received my doctorate.
• Aug, 2020 Began work at Delphi, helping build COVID forecasting models and engineering epidata pipelines.
• Oct, 2019 Attended GeoVet 2019. James presented our work on scan statistics epidemiology.
• Aug, 2019 Presented a poster at KDD2019 in Anchorage, Alaska.
• Summer, 2019 Started a project to apply scan statistics to epidemiology with Beatriz Lopez and James Sharpnack.
• Mar, 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.
• 2018-2019 Organized the reading group “Information Theory and Statistics”.
• Jul, 2018 Gave a talk on “Statistical Limits in Hierarchical Communication” in the Student Chapter Presentations section at the 2018 SIAM Annual Meeting in Portland, Oregon.
• Jun, 2018 Passed my qualifying exam with a proposal titled “Towards Statistical Limits in Hierarchical Communication”.
• Summer, 2017 Participated in the Machine Learning Summer Program at Los Alamos National Lab. I studied parameter learning in models of power transmission with Marc Vuffray and Andrey Lokhov. Our paper was accepted to PSCC2018: “Online Learning of Power Transmission Dynamics”.
• Jan, 2017 Co-organized the Davis Math Conference, a conference for professors and students to communicate their research in the Davis Math department.
• 2014-2016 Studied the inference of stochastic processes with memory, using Hidden Markov Models, information theory, and computational mechanics with Jim Crutchfield.

Courses Taught as Teaching Assistant

• MAT135 Probability and Stochastic Processes
• MAT129 Fourier Analysis
• MAT125 Real Analysis
• MAT108 Logic and Proofs
• MAT22 Linear Algebra and Differential Equations
• MAT21 Calculus