About

I am a Research Mathematical Statistician in the Center for Statistical Research and Methodology at the U.S. Census Bureau.

I recieved my PhD in statistics from the University of Washington in June 2023. I was advised by Arun Chandrasekhar at Stanford University and Tyler McCormick at UW. Previously I was a Fulbright Scholar at the University of Luxembourg and before that I received my BS in math from Arizona State University. At UW, I was supported by an ARCS fellowship.

I use tools from statistical inference and machine learning to answer questions in causal inference, network analysis, and survey design. A large part of my research focuses on making large-scale surveys more accessible to researchers by making them cheaper, more accurate, and easier to run. I work on model selection for network data and learning geometric properties of data to improve down-stream tasks in inference and machine learning. I develop user-friendly software that allows researchers to better understand their data.

A description of some of my work with Tyler McCormick recently appeared in the Wall Street Journal!

Email / CV / Google Scholar / GitHub

News

• October 13,2023: Our paper Bayesian Hyperbolic Multidimensional Scaling was accepted to the Journal of Computational and Graphical Statistics.
• October 13, 2023: Here is an interactive description of our recent work that appeared in PNAS.
• June 21, 2023: I will be serving as a mentor for the INSPIRE U2 REU program at Spelman College this summer!
• June 10, 2023: I received my PhD in Statistics from the University of Washington!
• March 23, 2023: Our paper on using Aggregated Relational Data to estimate network properties was accepted to PNAS!
• December 13, 2022: Our paper on latent space geometry was accepted to JRSS Series B!
• November 18, 2022: I am giving a talk at the Pioneer Center for AI at the University of Copenhagen.
• April 27, 2022: We have posted an updated version of our paper “Consistently estimating network statistics with aggregated relational data” to arXiv.
• November 17, 2021: I will be giving a presentation at the International Society of Bayesian Analysis in June 2022 on our geometry of latent space paper!
• November 12, 2021: I am excited to announce that I received the Z.W. Birnbaum award for best general exam in the past year. Thanks to my great advisors Arun and Tyler!
• October 20, 2021: We have posted an updated version of our paper “Consistently estimating network statistics with aggregated relational data” to arXiv.
• June 17, 2021: Our pre-print on spectral goodness-of-fit tests for complete and partial network data is out today! Check out the pre-print, code, and short summary.