Micah Goldblum is an assistant professor at Columbia University. His research focuses on both applied and fundamental problems in machine learning including AI safety, automated data science, training and inference strategies for large-scale models, and building a mathematical and also scientific understanding of why complex AI systems work. Micah’s portfolio includes work in Bayesian inference, generalization theory, algorithmic reasoning, and AI security and privacy. Before his current position, Micah was a postdoctoral research fellow at New York University working with Yann LeCun and Andrew Gordon Wilson. He previously received a Ph.D. in mathematics at the University of Maryland where he worked with Tom Goldstein and Wojciech Czaja.