Doctoral Lecturer, Data Science and Information Systems
George Hagstrom is a Doctoral Lecturer in Data Science and Information Systems at CUNY SPS.
His primary objective is to help students achieve their goals through building quantitative, statistical, and computational skills, and through sharing his experiences working in different disciplines and using diverse tools.
Additionally, Hagstrom performs research that explores emergence in ecology and other complex systems. Broadly, these questions are inspired by statistical physics and center around how the interplay among physiological constraints and evolutionary dynamics give rise to macroscopic function features and fluxes in ecosystems. To accomplish this, Hagstrom develops trait-based models of marine phytoplankton and heterotrophic bacteria and applies them to improve our understand of biogeochemical cycling and marine ecosystems. Hagstrom is also interested in the application of Bayesian statistics and Machine Learning to incorporate nontraditional datasets (such as from ’omics) into mechanistic models of marine ecosystems and biogeochemical cycling and critical transitions in complex ecological, social, or economic systems. Prior to joining CUNY, Hagstrom earned a PhD in Physics from the University of Texas at Austin, worked as a postdoctoral researcher in the Magneto-Fluids Division at the Courant Institute for Mathematical Scientists, and was a Research Scientist at Princeton University in the Levin lab at the Department of Ecology and Evolutionary Biology.