Complex event recognition
Detecting meaningful complex event patterns across high-volume, continuously evolving streams.
I work at the intersection of artificial intelligence, complex event recognition, temporal logics, and neurosymbolic learning to build systems that understand evolving phenomena.
Detecting meaningful complex event patterns across high-volume, continuously evolving streams.
Representing instantaneous and durative phenomena across past and future.
Combining the adaptability of neural learning with the clarity of rule-based reasoning.
Adapting predictive models over continuously changing streaming data.
Event-processing methods for maritime situational awareness and recognition of composite maritime activities.
Service as a program committee member, reviewer, and artifact evaluator for international conferences in artificial intelligence, data mining, knowledge management, and formal methods.
Manolis Pitsikalis is an AI researcher working on complex event recognition and forecasting, temporal logic, stream reasoning, and neurosymbolic AI. He received his PhD from the University of Liverpool, where his research combined logic-based methods and machine learning for real-time analysis, with a particular focus on maritime surveillance. He has held research positions at NCSR Demokritos and the University of Liverpool, and was a visiting researcher at the NATO Centre for Maritime Research and Experimentation. He has also taught Logic Programming and Software Engineering at the National and Kapodistrian University of Athens and supervised undergraduate/postgraduate research projects.