Machine Intelligence and Robot Learning (MIRL)
The Machine Intelligence and Robot Learning (MIRL) Lab at the University of Ottawa develops data-efficient, safe, and adaptive machine learning systems, with a focus on reinforcement learning and deep learning for real-world applications.
Our research lies at the intersection of machine learning, robotics, and decision-making under uncertainty, with the goal of enabling intelligent agents to operate reliably in complex and dynamic environments.
Research Focus
Reinforcement Learning
- Goal-conditioned and model-based RL
- Continual RL
- Safe and reliable learning
- Sample-efficient exploration
- Sim-to-real transfer
Applications
- Robotics and autonomous systems
- Healthcare and biomedical systems
- Industrial automation
- AI for science, environment, and climate
People
Current Members
PhD Students
Alex De Furia
Vulnerability classification with large language models Co-supervised with Paula Branco, Guy-Vincent Jourdan
MSc Students
William Elliot Hamilton
Thesis: Model-based reinforcement learning for adaptive optics Co-supervised with Davide Spinello (uOttawa), Ross Cheriton (NRC)
Aahil Jivani
Thesis: Continual model-based reinforcement learning
Tanishk Nandal
Course-based: Exploration in RL with verifiable rewards for LLM reasoning Co-supervised with Katie Fraser (uOttawa)
Fengshou Xu
Course-based: Mask-based goal conditioning for guided object placement
Undergraduate Researchers
Yasmine Trigui
Privacy-preserving synthetic health data
Sama Al-Akashi
Privacy-preserving synthetic health data
Bogdan Dobrynin
Model-based continual reinforcement learning
Alumni
PhD Alumni
- Payam Parvizi (PhD, 2026)
Wavefront Sensorless Adaptive Optics for Free-space Satellite-to-Ground Communication using Online Reinforcement Learning
Co-supervised with Prof. Davide Spinello (uOttawa) and Prof. Ross Cheriton (NRC)
MSc Alumni
Fahim Shahriar (MSc, 2026)
Simplifying Goal Representations with Masks in Vision-based Reinforcement Learning
Co-supervised with Prof. Rupam Mahmood (University of Alberta / Amii)Alireza Azimi (MSc, 2026)
Reinforcement Learning for Robotics
Co-supervised with Prof. Rupam Mahmood (University of Alberta / Amii)Runnan Zou (MASc, 2024)
Reinforcement Learning in Wavefront Sensorless Adaptive Optics Systems
Co-supervised with Prof. Davide Spinello (uOttawa) and Prof. Ross Cheriton (NRC)
Undergraduate Alumni
Zahra Suleymanova (Research Assistant, 2026)
Beyond Information Sufficiency: Observation-Action Space Alignment in Robotic Reinforcement LearningVishal Bhrat (Research Assistant, 2026)
Beyond Information Sufficiency: Observation-Action Space Alignment in Robotic Reinforcement Learning
Selected Projects
(Coming soon — highlight key research projects, open-source work, and systems)
Join the Lab
We are always looking for motivated students interested in reinforcement learning, deep learning, and robotics.
Apply here
Prospective MSc and PhD students should indicate Colin Bellinger as their preferred supervisor when applying to uOttawa EECS.