Jacob Calvert
I am on the 2025–2026 academic job market!I’m interested in collective behavior, which I study using probability theory and data science. Lately, I’ve been working on a principle of nonequilibrium self-organization and investigating how the behavior of a collective depends on the number of its constituents.
I’m a postdoctoral fellow at Georgia Tech and a visiting postdoctoral fellow at the Santa Fe Institute. I spent Spring 2025 as the Berlekamp postdoctoral fellow at the Simons Laufer Mathematical Sciences Institute in Berkeley, CA.
For details on my academic background and experience as a professional data scientist, see my CV or About. For more on my research, check out my Google Scholar profile, Papers, or Posts.
Dana Randall and I generalize and prove the main claims of an emerging physical theory of nonequilibrium self-organization, called rattling theory, by interpreting its main claims in terms of Markov processes. The result is a principle that relates a local aspect of the dynamics to the global steady state. We apply it to random walks on random graphs, spin-glass dynamics, and models of ant colonies.
Clinical risk scores can cheat the AUC when the time that an adverse event occurs in a positive-class stay tends to exceed the duration of a negative-class stay. Risk scores should be compared to uniformly random scores that match their timing.
My latest paper introduces the concept of critical numerosity: A number of individuals above and below which the behavior of a collective qualitatively differs.
This post explains how the Markov chain dichotomy of transience and recurrence implies dichotomous behavior for certain models of collective motion.
This post highlights recent work which constitutes only the third rigorous result about planar diffusion-limited aggregation (DLA), a paradigmatic model of random, dendritic growth.