WNCG Student Wins Award for Paper on Epidemic Processes

Ph.D. student Jessica Hoffmann received second place in the INFORMS Nicholson Student Paper competition. She received the award for her recent paper "Learning Graphs from Noisy Epidemic Cascades" with her advisor, WNCG professor Constantine Caramanis.

Epidemics are a powerful framework for modeling human and computer viruses, as well as influence, rumors, information and disinformation. Hoffmann’s research develops algorithms to solve an inverse problem on graphs, in order to understand the precise spreading mechanisms.

According to the Nicholson website, "The George Nicholson Committee competition is held each year to identify and honor outstanding papers in the field of operations research and the management sciences written by a student."

For Hoffmann, it’s the chance to make a lasting impact that drives her work.

“I'm lucky in the sense that my research combines what I like to do—write rigorous (and fun!) mathematical proofs—with a feeling that the results are meaningful,” Hoffmann stated. “This particular paper shows that after an epidemic takes place you can figure out the entire underlying graph (how all the nodes are connected) based solely on an approximate knowledge of when each node became infected.” The work could expand our knowledge of how infectious diseases are spread.

Hoffmann is a 5^th-year Ph.D. student. Her research interests include epidemic processes, graph theory, high-dimensional statistics, machine learning, and applications to large-scale networks.