Dr Hafez is a New Frontiers Fellow/Tenure Track Assistant Professor of Machine Learning in the School of Electronics & Computer Science at the University of Southampton. His research lies at the intersection of machine learning, robotics, and neuroscience, with a focus on robot skill learning.
Before joining the University of Southampton in Jan 2024, he was a postdoctoral research associate at Universität Hamburg, Germany, working on crossmodal neurocognitive models of robot behavior. His research enabled a humanoid robot to read the intention behind unlabeled demonstrations and learn a growing set of skills over time and resulted in the development of the first memory-efficient experience replay solution to catastrophic forgetting in reinforcement learning, contributing to the advancement of the emerging research direction of continual robot learning. Prior to this, he completed his PhD in machine learning at Universität Hamburg, Germany, in May 2020, supported by the Deutscher Akademischer Austauschdienst (DAAD) doctoral scholarship. His PhD research led to the development of the first intrinsically motivated reinforcement learning algorithm to successfully train visuomotor policies from scratch on a humanoid robot in the real world.
He has authored papers published in top-tier international journals and conference proceedings in AI and Robotics, such as Neural Computing and Applications, Robotics and Autonomous Systems, IEEE Transaction on Cognitive and Developmental Systems, and IEEE/RSJ International Conference on Intelligent Robots and Systems. He is an active reviewer for Nature Scientific Reports, International Journal of Robotics Research, IEEE Transactions on Industrial Informatics, and IEEE Intl. Conference on Robotics and Automation and is on the Editorial Board of Frontiers in Robotics and AI and Frontiers in Neurorobotics. He also served as a PC member for the 32nd International Conference on Artificial Neural Networks and the IEEE RAS Summer School on Multi-Robot Systems in Singapore, 2016. He is recognized as a Global Talent under the Exceptional Promise category by the Royal Society in the United Kingdom (2023).