Panagiotis Symeonidis

Panagiotis Symeonidis is Associate Professor at the School of Information and Communication Systems Engineering, University of the Aegean, Greece. Before moving to Samos, he was Assistant Professor at the Faculty of Computer Science (scientific sector INF/01) of the Free University of Bolzano, Italy, till November 2020. Before moving to Bolzano he worked for 8 years as Adjunct Assistant Professor at the Department of Informatics of the Aristotle University of Thessaloniki, Greece. He received a B.Sc. degree in Applied Informatics from University of Macedonia at Thessaloniki in 1996. He also received a n M.Sc. degree in Information Systems from the same university in 2004. He received his Ph.D. in Web Mining and Information Retrieval for Personalization from the Department of Informatics of the Aristotle University of Thessaloniki in 2008. His research interests include web mining (usage mining, content mining and graph mining), information retrieval, collaborative filtering, recommender systems, social media in Web 2.0 and location-based social networks. He is co-author of 3 international books, 1 Greek book, 6 book chapters, 25 journal publications and 40 conference/workshop publications. His published papers have received more than 3000 citations according to google scholar. Recently, he recognized from AMiner among the Most Influential Researchers ( in the last decade to the field of Recommender Systems. Half of his journal publications were published in top or highly ranked journals. One third of his conference publications have been published in top or highly ranked conferences.  Lastly, he was enlisted in the top 2% of the most cited scientists in the world ( 


My vision for the next couple of years is to combine social media analytics, graph and stream mining algorithms together with recommender systems and apply them in domains such as online news media, tourism, Internet of Things, Privacy and Health Analytics, where the main problems are the “curse” of dimensionality and the need for real-time predictions along with explanations.