Maher Mesto
PhD Researcher
Autonomous Agents and Robotics Research Group
UNSW Sydney, Australia

Address
School of Computer Science and Engineering
Ainsworth Building (J17) - Desk 510-25
Kensington Campus
UNSW Sydney
NSW 2052, Australia

Contact
Email: m.mesto@unsw.edu.au

Research interests

• Reinforcement Learning
• Human-Robot Interaction, Cognitive Robotics
• Neural Networks / Deep Learning

Useful links

• LinkedIn profile
• OrcID profile

Short bio: Maher Mesto is a PhD researcher in the School of Computer Science and Engineering at UNSW Sydney, supervised by Dr Francisco Cruz. His research sits at the intersection of reinforcement learning and robotics, focusing on how agents combine guidance from multiple imperfect teachers under disagreement, drift, and uncertainty.

His current work studies teacher selection, advisor weighting, and adaptive multi-source fusion for human-centred robot learning. He has published at ACRA 2025 and AJCAI 2025, with his AJCAI paper receiving a Best Paper award. He also supports teaching for COMP9414 at UNSW.

Selected Publications	Web
Mesto, M., & Cruz, F. (2025, November). The Consensus Paradox: When Low Disagreement Leads to Catastrophic Failure in Multi-teacher Reinforcement Learning. In Australasian Joint Conference on Artificial Intelligence, (pp. 426-438). Singapore: Springer Nature Singapore. Best paper award.
Mesto, M., & Cruz, F. (2025). Conservative Bias in Multi-Teacher Learning: Why Agents Prefer Low-Reward Advisors. In Proceedings of the Australasian Conference on Robotics and Automation (ACRA), 2025.