François Rivest

Dr. François Rivest is an Associate Professor at Queen’s University, affiliated with the Department of Biomedical and Molecular Sciences (School of Medicine, Faculty of Health Sciences). He also holds cross-appointments in the School of Computing (Faculty of Arts and Science) and is a member of the Centre for Neuroscience Studies. His research focuses on machine deep reinforcement learning and animal interval timing, aiming to bridge computational neuroscience insights with advanced AI systems. He leads the Natural and Artificial Adaptive Intelligent Systems Laboratory.

Education:

• PhD in Computer Science (Computational Neuroscience/Machine Learning) – Université de Montréal (2010)
• MSc in Computer Science – McGill University (2002)
• BSc in Mathematics and Computer Science – McGill University (2000)

Research Interests: Dr. Rivest’s work integrates principles of animal learning, particularly reward-based systems and temporal cognition, into machine learning algorithms. Key areas include:

• Reinforcement learning frameworks inspired by dopamine signaling
• Drift-diffusion models for interval timing
• Adaptive representation construction in real-time systems
• Applications in smart homes, robotics, and neuroscience

Publications: Over 20 peer-reviewed articles (2001–2022) span computational neuroscience, reinforcement learning, and machine learning systems. Recent work includes modeling interval timing dynamics and applying reinforcement learning to smart home systems.

Lab & Affiliations: As Principal Investigator of the Natural and Artificial Adaptive Intelligent Systems Lab, he explores interdisciplinary AI applications. Collaborations include the Royal Military College of Canada (2010–present) and Queen’s University’s Center for Neuroscience Studies (2011–present).