Dr. Gilbert is the John C. Malone Professor of Statistics and Data Science at Yale University whose research develops randomized algorithms and rigorous mathematical foundations for extracting structure from massive, high-dimensional data. Her work bridges harmonic analysis, probability, and theoretical computer science with practical computation, spanning foundational contributions to sparse signal recovery and compressed sensing as well as applications in imaging, network analysis, biology, and materials science. Drawing on her experience at AT&T Labs–Research, where she developed algorithms for analyzing internet-scale data streams, she brings a distinctive focus on principled evaluation: designing frameworks that rigorously assess when computational and machine learning methods succeed, when they fail, and why. Within TEMPEST, her work centers on building the evaluation methodologies and computational infrastructure needed to compare closure models fairly and reproducibly across scales. She has an extensive record of mentoring PhD students, postdoctoral fellows, and undergraduates, with particular commitment to preparing mathematical scientists for careers spanning academia, industry, and the national laboratories.