Data-Driven Methods for Deploying AI

Abstract

This seminar explores statistical and data-driven methods for making AI systems robust when they move from simulation into physical environments. It covers domain shift, sensor noise, Bayesian estimation, and uncertainty-aware deployment for researchers working at the interface of AI and engineering.