Iraklis Varlamis
Professor
Research Field: Data Management
Email:
CV
Iraklis Varlamis is a Professor at the Department of Informatics and Telematics of HUA in the area of Data Management. He holds a Ph.D. from Athens University of Economics and Business, Greece, and an MSc in Information Systems Engineering from UMIST, UK. His research interests range from data mining and social network analytics to recommender systems for social media and real-world applications. He has more than 280 articles published in international journals and conferences, and more than 7500 citations to his work. He holds a patent from the USPTO and one from the Greek Patent Office for systems that analyze news articles and web documents. He is an IEEE member and a member of the ELLIS society. He is the scientific coordinator for HUA in several EU (H2020, ECSEL, REC) projects and has a leading role in national projects in collaboration with researchers from other HUA departments and other universities. He has been listed among the top 2% of most cited scientists globally in the field of AI, according to Stanford's list for 2023 and 2024.
Selected Publications
Linardakis, M., Varlamis, I., & Papadopoulos, G. T. (2025). Survey on Hand Gesture Recognition from Visual Input. IEEE Access, 13, 135373–135406.
Iliopoulos, A., Violos, J., Diou, C., & Varlamis, I. (2025). Feature bagging with nested rotations (FBNR) for anomaly detection in multivariate time series. Future Generation Computer Systems, 163, 10754
Sayed, A. N., Himeur, Y., Varlamis, I., & Bensaali, F. (2025). Continual learning for energy management systems: A review of methods and applications, and a case study. Applied Energy, 384, 125458.
Kontopoulos, I., Varlamis, I., Makris, A., & Tserpes, K. (2024). A spatio-temporal matrix representation for trajectory classification. In Proceedings of the 32nd ACM International Conference on Advances in Geographic Information Systems.
Davalas, C., Michail, D., Diou, C., Varlamis, I., & Tserpes, K. (2024). A rehearsal framework for computational efficiency in online continual learning. *Applied Intelligence*, 54(8), 6383–6399.
Rizou, S., Theofilatos, A., Paflioti, A., Pissari, E., Varlamis, I., Sarigiannidis, G., & Chatzisavvas, K. C. (2023). Efficient intent classification and entity recognition for university administrative services employing deep learning models. Intelligent Systems with Applications, 19, 200247.
Nasir, J. A., Khan, O. S., & Varlamis, I. (2021). Fake news detection: A hybrid CNN-RNN based deep learning approach. International Journal of Information Management Data Insights, 1(1), 100007. Elsevier. doi: 10.1016/j.jjimei.2020.100007
Iliopoulos, A., Violos, J., Diou, C., & Varlamis, I. (2025). Feature bagging with nested rotations (FBNR) for anomaly detection in multivariate time series. Future Generation Computer Systems, 163, 10754
Sayed, A. N., Himeur, Y., Varlamis, I., & Bensaali, F. (2025). Continual learning for energy management systems: A review of methods and applications, and a case study. Applied Energy, 384, 125458.
Kontopoulos, I., Varlamis, I., Makris, A., & Tserpes, K. (2024). A spatio-temporal matrix representation for trajectory classification. In Proceedings of the 32nd ACM International Conference on Advances in Geographic Information Systems.
Davalas, C., Michail, D., Diou, C., Varlamis, I., & Tserpes, K. (2024). A rehearsal framework for computational efficiency in online continual learning. *Applied Intelligence*, 54(8), 6383–6399.
Rizou, S., Theofilatos, A., Paflioti, A., Pissari, E., Varlamis, I., Sarigiannidis, G., & Chatzisavvas, K. C. (2023). Efficient intent classification and entity recognition for university administrative services employing deep learning models. Intelligent Systems with Applications, 19, 200247.
Nasir, J. A., Khan, O. S., & Varlamis, I. (2021). Fake news detection: A hybrid CNN-RNN based deep learning approach. International Journal of Information Management Data Insights, 1(1), 100007. Elsevier. doi: 10.1016/j.jjimei.2020.100007