Daniel Larremore

Daniel B. Larremore


Dr. Daniel Larremore is an Associate Professor in the Department of Computer Science and the BioFrontiers Institute at the University of Colorado Boulder. He is also an affiliate of the Department of Applied Mathematics at the University of Colorado Boulder, and is a member of the external faculty at the Santa Fe Institute and in the Center for Communicable Disease Dynamics at the Harvard T. H. Chan School of Public Health. His research develops mathematical methods using novel combinations of networks, dynamical systems, and statistical inference to solve problems in two main areas: infectious disease epidemiology and computational social science. Prior to joining the University of Colorado faculty, he was an Omidyar Fellow at the Santa Fe Institute 2015-2017 and a post-doctoral fellow at the Harvard T.H. Chan School of Public Health 2012-2015. He obtained his Ph.D. in Applied Mathematics from the University of Colorado Boulder in 2012, and holds an undergraduate degree in Chemical Engineering from Washington University in St. Louis. He is the recipient of the Erdős–Rényi Prize from the Network Science Society and the Alan T. Waterman Award from the National Science Foundation.

Research Interests

  • Malaria's antigenic variation and evolution - The var genes of the malaria parasite P. falciparum evolve according to complicated and unknown rules, with selective pressures at multiple scales both within hosts and between hosts. I create and use mathematical tools to understand the structural and evolutionary constraints on var gene evolution, and their relationships with parasite virulence, population structure, and epidemiology.
  • Networks and theory - The processes that generate complex networks leave hints about themselves in the patterns of edges, and the relationships between those patterns and vertex metadata. I work on mathematical descriptions of graph ensembles, inference of community structures, vertex ordering or ranking, and using metadata to better understand network formation.
  • The scientific ecosystem - The scientific method of hypothesis, experiment, and conclusion poorly describes modern scientific discovery and productivity. Instead, science is done by people who play various social roles in the ecosystem of science. I investigate faculty hiring, productivity patterns, scientific careers, and the dynamics of discovery through large-scale data collection and modeling.

Outside the Lab

I lean in to Boulder stereotypes by climbing, mountain biking, running, and skiing. Boulder is a beautiful place to live, so I try to get outside a lot. I like to read, usually in a cycle consisting of nonfiction, literature, and science fiction. When I have time, I like to make art, typically sculpture with paper. If I had to do another job outside of science, I think I’d like to be a writer.