Intelligent Anomaly Detection in UAV Swarms Using Graph Attention and RSSI Signals
The IEEE University of Strathclyde Student Branch is pleased to host Dr. Ghulam E. Mustafa Abro (Senior Member, IEEE) for a special invited lecture on intelligent anomaly detection in autonomous UAV swarms.
Unmanned Aerial Vehicle (UAV) swarms are increasingly used in applications such as surveillance, disaster response, environmental monitoring, and autonomous logistics. However, ensuring reliability and safety in large-scale multi-agent systems remains a significant challenge. Detecting abnormal behaviour within distributed UAV networks is critical to maintaining robust and secure operations.
In this talk, Dr. Abro will present advanced approaches for intelligent anomaly detection in UAV swarms, leveraging Graph Attention Networks (GAT) and RSSI signal analysis. The discussion will explore how machine learning and network signal features can be combined to identify irregular behaviour patterns and enhance situational awareness in autonomous aerial systems.
Participants will gain insight into modern AI techniques applied to swarm intelligence, distributed robotics, and autonomous system monitoring.
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Dr. Abro
Intelligent Anomaly Detection in UAV Swarms Using Graph Attention and RSSI Signals
Unmanned Aerial Vehicle (UAV) swarms are increasingly used in applications such as surveillance, disaster response, environmental monitoring, and autonomous logistics. However, ensuring reliability and safety in large-scale multi-agent systems remains a significant challenge. Detecting abnormal behaviour within distributed UAV networks is critical to maintaining robust and secure operations.
In this talk, Dr. Abro will present advanced approaches for intelligent anomaly detection in UAV swarms, leveraging Graph Attention Networks (GAT) and RSSI signal analysis. The discussion will explore how machine learning and network signal features can be combined to identify irregular behaviour patterns and enhance situational awareness in autonomous aerial systems.
Participants will gain insight into modern AI techniques applied to swarm intelligence, distributed robotics, and autonomous system monitoring.
Biography:
Dr. Ghulam E. Mustafa Abro (Senior Member, IEEE)
Researcher, Artificial Intelligence in Robotics Laboratory (AiR Lab)
Department of Electrical and Computer Engineering
Aarhus University, Denmark
Dr. Abro is a distinguished academician and researcher specialising in autonomous systems, swarm intelligence, and robotics control. He is currently a researcher at the Artificial Intelligence in Robotics Laboratory (AiR Lab) at Aarhus University, Denmark.
Previously, he served as an academic affiliate with the Aerospace Engineering Department at King Fahd University of Petroleum and Minerals (KFUPM), Saudi Arabia, and as a postdoctoral researcher at the Interdisciplinary Research Centre for Aviation and Space Exploration.
His research focuses on mechatronic systems, dynamics and control, robotic motion planning, autonomous multi-agent systems, and AI-driven perception, contributing to real-world autonomous solutions through swarm intelligence and multi-agent architectures.
Dr. Abro received the Late Prof. Peter B. Luh Memorial Young Research Award at IEEE CASE 2024 in Bari, Italy, recognising his contributions to robotics and control. In 2025, he was also awarded the Best Research Excellence Award for robotics and control research at KFUPM, presented by Dr. Charles Elachi (Caltech, former Director of NASA’s Jet Propulsion Laboratory).