Address

University Hill, Mytilene 81100, Lesvos, Greece

Contact Information

Call: +30 22510 36620

Email: kotis@aegean.gr

Research Interests

  • AI chatbots
  • CMS
  • Cultural Informatics
  • Digital Culture
  • IoT
  • Knowledge Representation
  • Linked Data
  • Semantic trajectories
  • Semantic Web
  • Web app

Konstantinos Kotis

Assistant Professor, Team Leader (since 2019)

Dept. of Cultural Technology and Communication, University of the Aegean

Assist. Prof. Konstantinos Kotis (https://gr.linkedin.com/in/kotis, http://i-lab.aegean.gr/kotis) owns a BSc in Computation from University of Manchester, UK and a PhD in Information Management (Knowledge Representation/Management) from the University of the Aegean, Greece. He worked as a post-doc researcher and adjunct lecturer/professor at the AI Lab of the University of the Aegean (2015-2010), at VTT Technical Research Centre of Finland (2011-2012) as an ERCIM “Allain Bensoussan” post-doc fellow, and a post-doc researcher at the AI Lab of the University of Piraeus (2013-2018). He is currently an assistant professor at the University of the Aegean, Dept. of Cultural Informatics and Communication and a research associate at the University of Piraeus, Dept. of Digital Systems (AI Lab). His research interests include but not limited to Knowledge Engineering, Semantic Web and Internet of Things. He has published more than 60 papers (Google Scholar h-index 16, >1100 citations) in peer-reviewed international journals (incl. IJDST, KAIS, ILE, IJKEDM, FGCS, IEEE IS, IJWGS, IJMSO, Applied AI) and conferences (incl. ESWC, ISWC, KSEM, IJCAI, VLDB) and served as reviewer and PC member in several journals and conference events (incl. IEEE IS, IEEE TKDE, KAIS, JWS, J.UCS, IJDMMM, ICTAI, IJCAI). He has also participated in several national and international projects, including among them, Grid4All (FP7, 2008), iCore (FP7, 2012), Internet of Things (Finnish Tivit/Tekes, 2012), AMINESS (Greek, Research & Technology General Secretary. 2014), datACRON (H2020 ICT, 2016), Time Machine (H2020, 2019). ORCHID: https://orcid.org/0000-0001-7838-9691.

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