Alexandros Artikis is an substitute professor at the University of Piraeus and a Collaborating researcher at NCSR "Demokritos" , where he is responsible for the Complex Event Recognition team. He holds a PhD in distributed Artificial intelligence from Imperial College London. Dr.Artikis has more than 100 publications in artificial intelligence and science journals and conferences Journal of Artificial Intelligence Research, Machine Learning, IEEE Transactions on Knowledge and Data Engineering, Artificial Intelligence, ACM Transactions on Autonomous and Adaptive Systems, ACM Transactions on Computational Logic, ACM Transactions on Intelligent Systems and Technology, ACM Transactions on Internet Technology and VLDB Journal.
Identification and prediction of complex events
Complex Event recognition" systems aim to infer "complex" events from low-level data flows, using algorithms based on matching time patterns. These systems have many applications. For example, in the maritime sector illegal or dangerous ship behaviors are discovered from sensor data describing the course of those ships. In addition, with regard to health sciences, these tools can discover effective drug combinations from cancer cell simulations, thus facilitating and accelerating the work of scientists. In this talk we will present two representative systems of recognition and prediction of complex events, which have been developed using mathematical logic and automata theory. In addition, we will show the implementation of these systems in real applications
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