Ali Ayub

Dr. Ali Ayub is an Assistant Professor at the Concordia Institute for Information Systems Engineering (Concordia University). His research focuses on advancing human-robot interaction through continual learning and interactive machine learning, particularly in domains like healthcare, household assistance, and collaborative robotics. He investigates how robots can adapt to user preferences over time and learn from limited human input in dynamic environments.

Research Interests

His core interests span Artificial Intelligence, Interactive Machine Learning, and Continual Learning, with applications to Human-Robot Interaction, Robotics, and Computer Vision. He explores topics such as:

• Long-term personalization of robots through user feedback
• Adaptive learning architectures for home service and assistive robots
• Cognitive models for incremental learning in robotics
• Human teaching patterns and trust dynamics in HRI

Key Research Trends

His recent work emphasizes few-shot learning for robots to acquire new tasks with minimal demonstrations and continual learning frameworks that avoid catastrophic forgetting. He also studies how robots can interactively gather data through curiosity-driven exploration and adapt to human preferences in collaborative tasks. His projects often bridge theory (e.g., Markov decision processes for deceptive robotics) with practical applications like grocery reminder robots and episodic memory systems for companion robots.

Grants & Advising

No specific grants or advising information is provided in the text, but his prolific publication record suggests sustained research activity in these areas.