Prof. Konstantinos Diamantaras | International Hellenic University | Greece
Prof. Konstantinos Diamantaras is a Professor at the International Hellenic University, Department of Information & Electronic Engineering, and Vice Rector since 2023, holding a Beng from NTUA, Greece, and an MSc and PhD in Electrical Engineering from Princeton University. His research focuses on machine learning, signal processing, and augmented/virtual reality, with over 230 scientific publications and 79 journal articles indexed in SCI and Scopus, accumulating more than 7,300 citations on Google Scholar (h-index 30) and 3,027 citations on Scopus (h-index 23). He has authored four books, including Principal Component Neural Networks (1996) and Artificial Neural Networks (2007), and received the IEEE Best Paper Award in 1997 for Adaptive Principal Component Extraction (APEX). He leads multiple EU- and university-funded projects, such as Kids Radio Europe, METACHEF, Digital4all, and AI-based food recognition. His collaborations include Prof. S. Y. Kung (Princeton), Prof. Athina Petropulu (Rutgers), Prof. Tomas McKelvey (Chalmers), and partnerships with Alzheimer Hellas and the University of Alicante on NLP applications. He serves on editorial boards of Journal of Signal Processing Systems and Applied Sciences, contributing to advancements in deep learning, pattern recognition, biomedical informatics, adaptive signal processing, and educational technology. His work spans practical AI applications in health, digital learning, and immersive experiences, influencing both academic research and societal impact. He is an active IEEE member and IEEE Signal Processing Society participant, advancing knowledge in neural networks, computational intelligence, and multilingual natural language generation.
Profiles: Scopus | Orcid | Google Scholar | Staff Page
Featured Publications
Diamantaras, K. I., & Kung, S. Y. (1996). Principal component neural networks: Theory and applications. In Adaptive and learning systems for signal processing, communications, and control (p. 1694). Springer.
Vafeiadis, T., Diamantaras, K. I., Sarigiannidis, G., & Chatzisavvas, K. C. (2015). A comparison of machine learning techniques for customer churn prediction. Simulation Modelling Practice and Theory, 55, 1–9
Giatsoglou, M., Vozalis, M. G., Diamantaras, K., Vakali, A., & Sarigiannidis, G. (2017). Sentiment analysis leveraging emotions and word embeddings. Expert Systems with Applications, 69, 214–224.
Lampropoulos, G., Keramopoulos, E., Diamantaras, K., & Evangelidis, G. (2022). Augmented reality and gamification in education: A systematic literature review of research, applications, and empirical studies. Applied Sciences, 12(13), 6809.
Maglaveras, N., Stamkopoulos, T., Diamantaras, K., Pappas, C., & Strintzis, M. (1998). ECG pattern recognition and classification using non-linear transformations and neural networks: A review. International Journal of Medical Informatics, 52(1–3), 191–208.
Gravanis, G., Vakali, A., Diamantaras, K., & Karadais, P. (2019). Behind the cues: A benchmarking study for fake news detection. Expert Systems with Applications, 124, 292–303.
Kung, S. Y., & Diamantaras, K. I. (1990). A neural network learning algorithm for adaptive principal component extraction (APEX). In ICASSP-90. Acoustics, Speech, and Signal Processing (pp. 256–259).
Kung, S. Y., Diamantaras, K. I., & Taur, J. S. (1994). Adaptive principal component extraction (APEX) and applications. IEEE Transactions on Signal Processing, 42(5), 1202–1217.
Stamkopoulos, T., Diamantaras, K., Maglaveras, N., & Strintzis, M. (1998). ECG analysis using nonlinear PCA neural networks for ischemia detection. IEEE Transactions on Signal Processing, 46(11), 3058–3067.