Salem Lahlou

Bio: Salem Lahlou is an Assistant Professor in the Machine Learning Department at Mohamed bin Zayed University of Artificial Intelligence (MBZUAI). His research focuses on AI for science tools, including uncertainty quantification, sample efficient reinforcement learning, and large language model reasoning. He leads work on GFlowNets, a novel class of generative models for compositional objects with applications in scientific discovery. He holds a Ph.D. in uncertainty modeling from Université de Montréal and completed his master’s degrees at École Normale Supérieure (MVA) and École Polytechnique. His industry experience includes roles at TII, Google, IBM, and Booking.com. Through his research, Salem Lahlou aims to bridge the gap between theoretical advances in machine learning and practical applications in scientific discovery, while maintaining a deep interest in understanding both human and artificial intelligence.