Address
Department of Cultural Technology and Communication (D.C.T.C.)
University of the Aegean, University Hill
Administration Building, P.O. Box 81100, Mytilene
Konstantinos Michalakis
Konstantinos Michalakis holds a PhD at the Department of Cultural Technology and Communication (DCTC) with the title: “Context Awareness and Interaction on the Internet of Things” from 2022. In 2015, he acquired the Master’s Degree “Cultural Informatics and Communication” of DCTC. In 2003, he graduated from the Department of Computer Engineering and Informatics of the Polytechnic School of the University of Patras. He is currently working as a professor of Informatics in secondary schools of Lesvos prefecture since 2006. In the past (2004-2006) he has worked as IT Executive at Printec SA, Athens.
In recent years, Konstantinos Michalakis has also supported undergraduate students while supervising the preparation of postgraduate theses. He has also served as substitute professor at DCTC during 2023, teaching the following courses: “Advanced Artificial Intelligence” and “Data mining”. He is currently a postdoctoral researcher at DCTC, exploring “Context awareness in ubiquitous environments”.
Konstantinos Michalakis has participated in the implementation of various projects in the fields of cultural heritage and the integration of machine learning techniques. More specifically, he was involved in the implementation of machine learning algorithms and models for the PaloAnalytics project. He was also involved in the implementation of CultKiosk, a complete platform of cultural heritage management. Currently, he is participating in the concluding research activities of StreetLines project which applies machine learning techniques on touristic data.
He has published articles in journals and conferences related to research interests such as: Internet of Things – Pervasive Computing, Context Awareness, Semantic Web, Smart Home – Office – City, Smart Interfaces, Smart Health – Ambient Assisted Living, Augmented Reality, Linked Data, User Experience, Sentiment Analysis, Machine Learning, Data Mining.