Daniel Larremore, an associate professor of computer science at CU Boulder, was awarded the prestigious Erdős–Rényi Prize in network science today in Vienna, Austria, for his internationally recognized work on COVID-19 and network epidemiology.
The Erdős–Rényi Prize is an annual award for young scientists under 40 in the field of network science. It recognizes outstanding contributions, both theoretical and experimental, that promote interdisciplinary progress. The prize includes a cash award, a personalized plaque and a prize lecture at the NetSci International School and Conference on Network Science.
Larremore was nominated for the prize by Mason Porter, professor of mathematics at University of California, Los Angeles; Alessandro Vespignani, professor of physics at Northwestern University; and Aaron Clauset, professor of computer science at CU Boulder.
"This is the top prize for early-career scientists in network science, and reflects Dan’s outstanding work on the role of networks in epidemiology and in developing powerful new methods for untangling complex network structures," said Clauset, who was awarded the Erdős–Rényi Prize in 2016, making CU Boulder the only institution in the world with multiple awardees.
Network science is a multidisciplinary field focused on understanding and leveraging the way interactions drive the structure and dynamics of diverse complex networks, such as social, biological and technological systems. The field has shed new light on how infectious diseases spread, on the resilience of ecosystems, and on how information diffuses across social networks, yielding new tools to predict and comprehend cross-network consequences.
Larremore, collaborating with members of his lab and partners at other institutions, played a vital role in addressing the COVID-19 pandemic. His work analyzing different vaccine prioritization strategies, published in Science magazine, informed the global policies of the World Health Organization. In 2022, he received the NSF Alan T. Waterman Award for this work, which is the nation’s highest honor for early career scientists in any field of study.
While Larremore's lab primarily focuses on developing statistically sound models to comprehend intricate biological and social systems, the lab’s broad expertise is evident in its collaborative work published in Nature, exploring hierarchy and dynamics in U.S. faculty hiring and retention.