Tim Molloy

I develop theory and algorithms for decision-making with incomplete, costly, or strategically hidden information. My research combines control, information theory, game theory, artificial intelligence, and machine learning to understand how decision-makers, including robots and uncrewed aircraft, can learn objectives, decide what to observe, detect changes, and act in uncertain environments. My recent work has focused on inverse optimal control, partially observed Markov decision processes (POMDPs), quickest change detection, dynamic and differential game theory, and event-based sensing and perception.

I am currently a Senior Lecturer in the Department of Electrical and Computer Systems Engineering at Monash University, Australia. Prior to joining Monash, I was a Senior Lecturer (Mechatronics) in the School of Engineering at the Australian National University (ANU), a Research Fellow at the University of Melbourne, and an Advance Queensland Research Fellow at Queensland University of Technology (QUT), where I was embedded with Boeing Research & Technology Australia. I received the B.E. degree in Aerospace Avionics and the Ph.D. degree in Robotics and Autonomous Systems from QUT.

Prospective Students: I am actively recruiting PhD and project students. Please email me if you are interested.