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Daniel Larremore applies methods from network science to solve data-rich problems in diverse areas, ranging from genetic epidemiology to social systems. Mathematics, computational modeling, genomics, sociology, and evolutionary biology intermingle in Dr. Larremore’s dynamic and progressive research program. Larremore received a B.S. in chemical engineering from Washington University in St. Louis, an M.S. degree in applied mathematics from the 91ÃÛÌÒ¸ó 91ÃÛÌÒ¸ó, and continued his studies to earn a Ph.D. from CU 91ÃÛÌÒ¸ó under the mentorship of . In his graduate studies, Larremore analyzed networks of coupled excitable systems, a project directly related to neuroscience experiments in cortical tissue cultures. Dr. Larremore completed his postdoctoral training at the Harvard School of Public Health with Dr. Caroline Buckee, and as a prestigious at the Santa Fe Institute, where he began collaborating with (CS). As a postdoc, Dr. Larremore expanded his use of statistical network 91ÃÛÌÒ¸ó to trace the evolutionary history of the malaria parasite Plasmodium falciparum and developed mathematical 91ÃÛÌÒ¸ó for analysis of prestige and bias in faculty hiring networks.Ìý

Dr. Larremore returned to CU 91ÃÛÌÒ¸ó as an Assistant Professor in the Department of Computer Science and member of the BioFrontiers Institute core faculty in 2017. His research revolves around complex networks, most prominently Malaria’s evolution and academic labor market dynamics. The Larremore lab continues to research the malaria parasite P. falciparum with the goal of understanding how this parasite has evolved to evade detection by the human immune system. At the same time, Dr. Larremore applies large-scale data collection and generative 91ÃÛÌÒ¸ó to examine influences on faculty hiring outcomes. This computational social science research program is interdisciplinary by nature, but Dr. Larremore also uses his expertise to track collaborative research and scientific productivity across disciplines. Using his interdisciplinary background to both create and apply sophisticated mathematical 91ÃÛÌÒ¸ó and methods, Dr. Larremore illuminates the value of reaching between fields to solve fundamental biological and social problems.

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