Amir-massoud Farahmand

Vector Institute, University of Toronto

Title:Approximate Dynamic Programming and Batch Reinforcement Learning


Amir-massoud Farahmand is a faculty member, research scientist, and Canada CIFAR AI Chair at the Vector Institute in Toronto, Canada. He is also an assistant professor (status) at the Department of Computer Science, University of Toronto, with a cross-appointment at the Department of Mechanical and Industrial Engineering. His research interests are in reinforcement learning and machine learning with a focus on developing theoretically-sound algorithms for challenging industrial problems. He received his PhD from the University of Alberta in 2011, followed by postdoctoral fellowships at McGill University (20112014) and Carnegie Mellon University (CMU) (2014). Prior to joining the Vector Institute in 2018, he worked as a principal research scientist at Mitsubishi Electric Research Laboratories (MERL) in Cambridge, USA for three years.