Jessica Hoffmann is a 5th-year PhD Student at UT Austin, working with Constantine Caramanis. She works on epidemic processes on graphs, with a focus on noisy observation models (such as those in which the infected status of nodes is uncertain or the time of infection is noisy).
Her research interests include: epidemic processes, graph theory, high-dimensional statistics, machine learning, and applications to large-scale networks. She is also interested in convex and nonconvex optimization, robust statistics, and learning theory.
She received her Master’s degree from Ecole Normale Supérieure in Paris.