Jed is a master’s student working with Empirical Inference at the Deep Models & Optimization group. His thesis focuses on the theory of discrete diffusion; but his interests extend to differential privacy, optimization, and statistical learning theory. He is a relAI scholar at TUM and recently completed a research internship at the University of Alberta.