Jacob Calvert
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 the Institute for Data Engineering and Science at Georgia Tech. I’ll spend 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 About. For more on my research, check out Papers or Posts.
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.