Panagiotis Symeonidis

Panagiotis Symeonidis is Associate Professor at the School of Information and Communication Systems Engineering of the Aegean University, Greece from November 2020. Before, he was Assistant Professor at the Faculty of Computer Science (scientific sector INF/01) of the Free University of Bolzano, Italy, from November 2016 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 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, personalized health, recommender systems, and social media analytics. He is co-author of almost 100 publications and the first author in more than 50 publications. His publications are analysed in 4 international books, 2 Greek books, 6 book chapters, 32 journal publications and 48 conference/workshop publications. His published papers have received more than 4000 citations and has an h-index = 33, according to Google Scholar. In 2017, he was recognized from AMiner among the Most Influential Researchers https://www.aminer.cn/ai10/recommendation of the last decade to the field of Recommender Systems. Two out of three of his journal publications were published in top-tier or highly ranked journals. One out of three of his conference publications have been published in top-tier or highly ranked conferences. Finally, he has been recognized as one of the top 2% of scientists globally for three consecutive years (2019, 2020, and 2021), a testament to the impact and influence of his research contributions in the fields of recommender systems and data science.

Keywords: AI and Data Science