Rate My Professor Essam Debie

Debie's research specializations encompass Human-Autonomy Interaction and Swarm Intelligence. His contributions include developing adaptive AI for modulating assistance based on cognitive workload using EEG and physiological signals, shepherding and coordination of UAV/UGV swarms, and trust architectures for human-swarm teaming. He has authored numerous peer-reviewed publications, including journal articles such as 'Task-focused robotic swarming: Maximising effectiveness via specialised roles' (2025, Robotics and Autonomous Systems), 'Why Autonomous Vehicles Are Not Ready Yet: A Multi-Disciplinary Review of Problems, Attempted Solutions, and Future Directions' (2025, Journal of Field Robotics), 'Swarm Robotics: A Survey from a Multi-Tasking Perspective' (2024, ACM Computing Surveys), 'Session Invariant EEG Signatures using Elicitation Protocol Fusion and Convolutional Neural Network' (2022, IEEE Transactions on Dependable and Secure Computing), 'Human-Swarm-Teaming Transparency and Trust Architecture' (2021, IEEE/CAA Journal of Automatica Sinica), and 'Multi-Modal Fusion for Objective Assessment of Cognitive Workload: A Review' (2019, IEEE Transactions on Cybernetics). Additional key works feature 'Electroencephalographic Workload Indicators During Teleoperation of an Unmanned Aerial Vehicle Shepherding a Swarm of Unmanned Ground Vehicles in Contested Environments' (2020, Frontiers in Neuroscience), 'Path Planning for Shepherding a Swarm in a Cluttered Environment using Differential Evolution' (2020, IEEE Symposium Series on Computational Intelligence), and book chapters like 'Transparent Shepherding: A Rule-Based Learning Shepherd for Human Swarm Teaming' (2021). Debie has also presented at conferences, including 'From Single-tasking Swarming to Multi-tasking Heterogeneous Swarming for Solving Non-uniform Area Coverage Problems' (2025, International Conference on Swarm Intelligence).