The 2020 annual flagship conference of the IEEE Intelligent Transportation Systems Society (ITSS) will be held in Rhodes, Greece. The International Conference on Intelligent Transportation Systems (ITSC) provides a stage for papers and presentations in the field of Intelligent Transportation Systems, dealing with new developments in theory, analysis, simulation and modeling, experimentation, demonstration, case studies, field operational tests, and deployments. ITSC 2020 particularly invites and encourages prospective authors to share their work, findings, perspectives and developments as related to implementation and deployment of advanced ITS applications.
The Big Data Stack Participation
Big Data Stack will participate in this great event with the presentation of a paper titled
- "Predictive maintenance leveraging machine learning for time-series forecasting in the maritime industry".
Dimosthenis Kyriazis is the technical coordinator of the BigdataStack project and Assistant Professor at University of Piraeus at the Department of Digital Systems. With a PhD in the area of Service Oriented Architectures, he is specialised in service-based, distributed and heterogeneous systems, software engineering and data management.
Stathis Plitsos is Head Of Development at @DeepSea Technologies.
Dr. Stathis Plitsos is a senior researcher and Head of Development at DeepSea Technologies, a proud member of Danaos Corporation. He holds a PhD in Operations Research and Decision Support Systems. He has worked in many national and European research projects. Over the past 2 years he focuses on IoT, big data optimization and AI approaches for the shipping industry.
|Georgios Makridis is a Machine Learning Researcher for the BigDataStack in the frames of him being a PhD Candidate at University of Piraeus in the area of Data Science. Employed as Supervisor at R&D Telecommunications Department of the HAF Depot, with over 10 years of experience in military telecommunications. Excellent reputation for resolving problems and driving operational improvements. He is specialised in Time-series forecasting and classification, Anomaly detection and generally applied ML/DL approaches in real life problems.
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