Dimitris Zissis is an Associate Professor at the University of the Aegean at the Department of Product & Systems Design Engineering. More recently he established the Smart Move Laboratory at the University of the Aegean in Syros (Greece), that undertakes research into autonomous vessels and marine robotics.
He has an interest in marine technology and maritime informatics, spatial analysis, autonomous systems, trajectory analytics, distributed computing and Big Data. His published scientific work includes more than 80 publications (scientific journals, books and conferences included), which have received more than 3900 citations to date. According to [1] he has is included in the top 2% of scientists internationally in the field of “Information Systems” for three consecutive years (2019, 2020, 2021), while according to Thomson Reuters, the paper “Addressing Cloud Computing Security Issues” is included in the top 0,1% percentile of publications internationally for 2010-2014 based on the citations it has received.
Throughout these years he has participated and led teams in numerous R&D projects funded by the EC and industry, with Horizon 2020 projects VesselAI, INFORE and BigDataOcean being the most recent ones. He was a member of the European Commission High-Level Expert Groups on Business-to-Government (B2G) data sharing and B2G data sharing for official statistics (B2G4S), and led the Task Force (Data Science/AIfor the Big Data Value Association (BDVA), the private counterpart to the EU Commission to implement the Big Data Value PPP program, for a number of years.
He is the National Representative to the Horizon Europe Programme Committee (PC) for “Cluster 4: Digital, Industry and Space”.
He is a member of the editorial board of Future Generation Computer Systems (FGCS) published by Elsevier and PC member for numerous conferences including CLOUDCOM, GECON, SerCO and others. Ηe is an IEEE Senior Member and a member of the IEEE Computer Society, IEEE Oceanic Engineering and the IEEE Intelligent Transportation Systems Societies and the Young Researchers Committee of the World Federation on Soft Computing. He is a fellow of the Hellenic Institute of Marine Technology. His professional experience includes senior consulting and researcher positions in a number of private and public institutions.
- G Spiliopoulos, K. Chatzikokolakis, D. Zissis, E. Biliri, D. Papaspyros, G Tsapelas, S. Mouzakitis, Knowledge extraction from maritime spatiotemporal data: An evaluation of clustering algorithms on Big Data, IEEE International Conference on Big Data (IEEE Big Data 2017), December 11-14, 2017, Boston, MA, USA.
- A Valsamis, K Tserpes, D Zissis, D Anagnostopoulos, T Varvarigou, Employing traditional machine learning algorithms for big data streams analysis: The case of object trajectory prediction, Journal of Systems and Software, Elsevier, 127, 249-257, 2017
- L. M. Millefiori, D. Zissis, L. Cazzanti and G. Arcieri, "A distributed approach to estimating sea port operational regions from lots of AIS data" IEEE International Conference on Big Data 2016 (IEEE Big Data 2016), Washington, DC, 2016, pp. 1627-1632
- Dimitrios Zissis, Elias K. Xidias, Dimitrios Lekkas, A cloud based architecture capable of perceiving and predicting multiple vessel behaviour, In Applied Soft Computing, Volume 35, 2015, Pages 652-661, ISSN 1568-4946, Elsevier
- Dimitrios Zissis, Dimitrios Lekkas, Addressing cloud computing security issues, In Future Generation Computer Systems, Volume 28, Issue 3, 2012, Pages 583-592, ISSN 0167-739X, https://doi.org/10.1016/j.future.2010.12.006.
Guide to Maritime Informatics
Editors: Artikis, Alexander, Zissis, Dimitris (Eds.)