Zachary Pisano is a lecturer in the Department Applied Mathematics and Statistics. His research focuses on model selection, extensions of Expectation-Maximization algorithm, and random graph inference. Currently he is working toward the unification of these topics via the development of evidence-based model-selection criteria for network data.
He received a BS in Statistics from Loyola University of Maryland in 2016, followed by an MSE in Applied Mathematics and Statistics from Johns Hopkins University in 2018. He successfully defended his PhD thesis “Towards an Occam Factor for Random Graphs” immediately before joining the department in July 2022.