Gurprit Singh is a senior researcher at the Max Planck Institute (MPI) for Informatics, where he is currently leading the sampling & rendering group. His research interests are in Markov Chain Monte Carlo (MCMC), diffusion models, noise correlations and Monte Carlo sampling for physically based (forward/inverse) rendering. He has published his research in the top-tier conferences like SIGGRAPH (North America/Asia), NeurIPS, ECCV and Eurographics. His current focus is on bridging the gap between physically based rendering and generative AI using the powerful machinery of MCMC methods.