Doina Precup

Doina Precup is a Chair in the Department of Computer Science at McGill University. Her research focuses on Machine Learning. She can be contacted via email at dprecup@cs.mcgill.ca, and her personal website is http://www.cs.mcgill.ca/~dprecup/.

Doina Precup is a researcher specializing in Artificial Intelligence, machine learning, and reinforcement learning. Her work focuses on advancing temporal abstraction frameworks, temporal-difference learning, and off-policy deep reinforcement learning. She has contributed to benchmarking multimodal brain tumor segmentation and exploring uncertainty measures in deep networks for medical imaging. Her research also includes scalable architectures for real-time learning and continual reinforcement learning. Precup's publications emphasize policy evaluation, eligibility traces, and the development of architectures like the option-critic. Her work bridges theoretical foundations with practical applications in reinforcement learning and multi-armed bandit problems.