About me

I am a second-year PhD student in the Department of Statistics & Data Science at Carnegie Mellon University. I received my BSc in Statistics and Economics from the Department of Statistics at NC State University in 2017.

As a member of CMU’s DELPHI group, my current research project is nowcasting influenza via digital surveillance data. I am broadly interested in data-driven decision-making, computational statistics, visualizations, and image processing.

This summer, I’m a motion planning intern for Argo AI building self-driving cars.


Previous work

I worked as an undergraduate research assistant at Laber Labs under the direction of Eric Laber in the Department of Statistics. I developed educational games demonstrating reinforcement learning algorithms. You can read about it in AMSTAT or play some of the games.

As an undergrad, I also worked on constructing prediction regions for multiple-objective Markov decision processes with Daniel Lizotte in the Department of Computer Science and Epidemiology & Biostatistics at the University of Western Ontario [1]. I was briefly an intern at Duke-National University of Singapore Medical School supervised by Bibhas Chakraborty working on estimating shared-parameter Dynamic Treatment Regimes.

Outside of academia, I prototyped anomaly detection methods for high-frequency machine generated data at SAS Institute [2, 3].