about
I am a Postdoctoral Scholar at Stanford University in the Economics Department, where I work with Arun Chandrasekhar. I study spectral methods for network analysis, causal inference, and causal inference on networks. In September 2026, I will join Oregon State University as an Assistant Professor in Statistics.
I completed my PhD in Statistics at the University of Wisconsin-Madison, where I was co-advised by Keith Levin and Karl Rohe. During my PhD I spent some time working on broom, a popular open-source R package in the tidyverse, and I interned at Posit (formerly RStudio) and Facebook.
I keep Google Scholar up to date. My intermittently updated curriculum vitae is available here.
Outside of academic life, I’m excited about trying new food, weightlifting, learning the guitar, and, intermittently, developing a better sense of style.
Lately I’ve been reading lots of speculative fiction, especially Ursula K. Le Guin, and getting into espresso.
I dabble in ultimate frisbee, pickleball and climbing, and am vaguely pondering social dance as my next underdeveloped hobby.
I love to host dinner parties, go on group bike rides, and watch chaos unfold during Blood on the Clocktower.
recent news
2026-07-29: I presented at New Researchers Conference 2026 about some recent work on estimating peer effects in noisy networks slide
2026-04-11: I presented on Spectral Estimation and Trait Selection for Aggregated Relational Data at Network Science in Economics 2026.
2026-04-09: I have a new working paper Estimating peer effects in noisy, low-rank networks via network smoothing with Keith Levin.
2025-12-15: I presented Minimax rates for the linear-in-means model reveal an identifiability-estimability gap virtually at CMStatistics 2025.
Material from older talks, presentations, posters, etc, can be found on my Github.
working papers & pre-prints
Estimating peer effects in noisy, low-rank networks via network smoothing. Alex Hayes and Keith Levin. arXiv. May 4, 2026. replication package
Minimax rates for the linear-in-means model reveal an identifiability-estimability gap. Alex Hayes and Keith Levin. arXiv. November 4, 2025. replication package
publications
Estimating network-mediated causal effects via principal components network regression. Alex Hayes, Mark M. Fredrickson, and Keith Levin. Journal of Machine Learning Research. 2025. replication package, code
Co-factor analysis of citation networks. Alex Hayes and Karl Rohe. Journal of Computational and Graphical Statistics. 2024. post-print, arXiv, replication package, code
Welcome to the tidyverse. Hadley Wickham, Mara Averick, Jennifer Bryan, Winston Chang, Lucy D’Agostino McGowan, Romain François, Garrett Grolemund, Alex Hayes, Lionel Henry, Jim Hester, Max Kuhn, Thomas Lin Pedersen, Evan Miller, Kirill Müller, David Robinson, Dana Paige Seidel, Vitalie Spinu, Kohske Takahashi, Davis Vaughan, Claus Wilke, Kara Woo, Hiroaki Yutani. Journal of Open Source Software. 2019. website
consulting
At Stanford, I do some informal statistical consulting in the economics department, especially for grad students. Learn more.
blog
In a hobbyist capacity, I also blog about statistics, programming, and data. Some posts I enjoyed writing: