He obtained his Ph.D. from Carnegie Mellon University in 2001. Professor Dellaert’s research focuses on probabilistic methods in Robotics and Computer Vision. His approach is to pair probabilistic, model-based reasoning with randomized approximation methods to attain efficiency. He has applied Markov chain Monte Carlo sampling methodologies in a variety of novel settings, including the Monte Carlo localization method for estimating and tracking the pose of robots, now a standard and popular tool in mobile robotics.