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ITCCS Research

The Department of Information Technology, Cybersecurity, and Computer Science is committed to pioneering research across a diverse range of dynamic fields, including cybersecurity, data privacy, artificial intelligence, machine learning, bioinformatics, network security, big data analytics, cloud computing, wireless networks, blockchain, gaming, and the Internet of Things (IoT). By fostering innovation, embracing diversity, expanding programs, and forging strong industry collaborations, we aim to thrive in the rapidly evolving technological landscape and drive meaningful advancements in both technology and higher education.

Applications of our research span from:

Artificial Intelligence

Pioneering AI models and algorithms to enhance decision-making, automate complextasks, and enable adaptive learning systems. Our research focuses on machinelearningoptimization, ethical AI frameworks, and intelligent systems that supportapplications across healthcare, finance, robotics, and more.

Bioinformatics and technology in Healthcare

Innovating digital health solutions, including AI-driven diagnostics, remote patientmonitoring, and personalized treatment plans to improve healthcare outcomes. Our research focuses on wearable technology, predicting drug-to-drug interactions, secure health data management, and telemedicine platforms, enhancing accessibility, efficiency, and precision in patient care across diverse settings. We also apply advanced genomics and other omics approaches, leveraging large-scale biomedical data to uncover insights critical to public health. By analyzing genomic, transcriptomic, proteomic, and metabolomic data, we aim to address key challenges in disease prevention, treatment, and health management on a global scale.

Blockchain

Exploring decentralized ledger technologies to enhance transparency, security, and efficiency across various sectors. Our research focuses on consensus algorithms, smart contract development, and secure data sharing frameworks, supporting applications in finance, supply chain management, healthcare, and digital identity verification for a more resilient and trustworthy digital infrastructure.

Computer Gaming

Enhancing gaming experiences through AI-driven mechanics, realistic simulations, and adaptive storytelling techniques. Our research explores real-time rendering, user experience optimization, and procedural content generation, supporting advancements in immersive gameplay, virtual reality environments, and gamification strategies for education and training.

Cybersecurity

Innovating protective measures and threat detection systems to safeguard digital infrastructure against evolving cyber threats. Our research focuses on advanced encryption methods, intrusion detection/prevention, and AI-driven anomaly detection, enhancing resilience across networks, cloud environments, and IoT systems while supporting privacy and regulatory compliance.

Governance

Researching and implementing cybersecurity governance frameworks to ensure that security policies align with organizational goals, risk management, and regulatory requirements.

Machine Learning

Developing advanced algorithms and models that enable data-driven insights, predictive analytics, and automation across various domains. Our research includes model interpretability, reinforcement learning, and scalability improvements, supporting applications in fields like finance, healthcare, manufacturing, and natural language processing to enhance decision-making and operational efficiency.

Privacy

Ensuring data protection, regulatory compliance, and the ethical use of personal data, focusing on GDPR, CCPA, DORA, and other privacy frameworks.

Wireless Networks

Developing next-generation wireless communication protocols and architectures to improve connectivity, reduce latency, and increase data transfer rates. Research includes innovations in 5G/6G technologies, spectrum optimization, and secure IoT network frameworks, enabling robust and scalable wireless infrastructure for diverse applications.

Current Research

Journal Publications in 2024

  • C. Akasiadis, E. Kladis, E. P. Kamberi, F. Michelioudakis, E. Alevizos, A. Artikis, “A Framework to Evaluate Early Time-Series Classification Algorithms,” In EDBT (pp. 623-635), 2024.

  • I.T. Christou, J. Soldatos, P. Lappas, “Trusted Artificial Intelligence for Industry 5.0 Applications based on Quantitative Explanations,” 2024, under review.

  • P. Mulinka, I.T. Christou, et al., “Towards High-Fidelity and Trustworthy Digital Twins for Fault Diagnosis in Grid Connected Inverters,” IEEE Transactions on Dependable & Secure Computing, Provisionally Accepted with Major Revisions, 2024.

  • A. Mylonas, J. Macia, T. Pean, N. Grigoropoulos, I. T. Christou et al., “Optimizing energy efficiency with a cloud-based model predictive control: a case study of a multi-family building,” Energies, Accepted with Minor Revisions, 2024.

  • Alexandros Papadakis, I. T.Christou, J. Soldatos, C. Ipektzidis, A. Amicone, “Explainable andTransparent Artificial Intelligence for Public Policy Making,” Data & Policy, https://doi.org/10.1017/dap.2024.3, 2024.

  • I.T.Christou, Eugenia Vagianou, George Vardoulias, “Planning Courses for Student Success at the American College of Greece,” INFORMS Journal on Applied Analytics, 54(4), https://doi.org/10.1287/inte.2022.0083, 2024.

  • I.T. Christou, A.G. Lagodimos, K. Skouri, “Fast Near-Optimal Determination of (s,S,T) Periodic Review Inventory Policy Parameters,” Intl. Journal of Systems Science: Operations & Logistics, 11(1): 2404666, https://doi.org/10.1080/23302674.2024.2404666, 2024.

  • P. K. Gkonis, S. Lavdas, G. Vardoulias, P. Trakadas, L. Sarakis and K.Papadopoulos, “System Level Performance Assessment of Large-Scale Cell-Free Massive MIMO Orientations With Cooperative Beamforming,” in IEEE Access, vol. 12, pp. 92073-92086, 2024, doi:10.1109/ACCESS.2024.3422349.

  • P. Gkonis, S. Lavdas, G. Vardoulias, P. Trakadas, L. Sarakis, and K. Papadopoulos, “Adaptive Beamforming, Cell-Free Resource Allocation and NOMA in Large-Scale Wireless Networks,” submitted on 10/2024.

  • A.J. Taylor, K. Yahara, L. Mageiros, et al. “Epistasis, core-genome disharmony, and adaptation in recombining bacteria.” MBIO, DOI:https://doi.org/10.1128/mbio.00581-24.

  • M. AlaaEldin, E. Alsusa, K. G. Seddik, M. Al-Jarrah and C. B. Papadias, “Optimization of Energy-Constrained IRS-NOMA Using a Complex Circle Manifold Approach,” in IEEE Internet of Things Journal, vol. 11, no. 20, pp. 33133-33150, Oct.15, 2024, doi: 10.1109/JIOT.2024.3427425.

  • G. A. Ropokis and P. S. Bithas, “Multi-Antenna Wireless Powered Relaying: Low Complexity and Near Optimal Techniques for Generic EH Models,” in IEEE Transactions on Green Communications and Networking, vol. 8, no. 2, pp. 686-700, June 2024.

  • P. S. Bithas, G. A. Ropokis, G. K. Karagiannidis and H. E. Nistazakis, “UAV-Assisted Communications With RIS: A Shadowing-Based Stochastic Analysis,” in IEEE Transactions on Vehicular Technology, vol. 73, no. 7, pp. 10000-10010, July 2024.

  • C. R. Gonzalez, E. Menasalvas, F. Aisopos, D. Vogiatzis et al., “Monitoring and Decision Support in Treatment Modalities for Lung Cancer,” Technology in Healthcare: Clinical Impacts, Workflow Improvement, Structuring and Assessment, Now Publishers(2024).

Conference Papers (Conferences in 2024)

  • E. Alevizos, G. M. Santipantakis, C.Doulkeridis, A. Artikis. “Online Integration of Spatial Reasoning in Complex Event Recognition,” In EDBT/ICDT Workshops 2024.

  • E. Alevizos, A.Artikis ,G. Paliouras “Complex Event Recognition with Symbolic Register Transducers,” Proceedings of the VLDB Endowment, 17(11), 3165-3177, 2024.

  • G.C. Giaconia, F.L.Valvo, K. Ladjery, F.D. Puma, J.Falla, I.T. Christou, J. Soldatos, T.Papadakis, B. Popunkiov, D. Alexieva, D. Raykov, “Vibration-based water leakage detection system for public open data platforms,” Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4/W10-2024, 71–76,2024.

  • A.E. Marchezan, I.T. Christou, P. Nardelli, M. Giesbrecht, “Fuel Adulteration Detection forOtto Cycle Vehicles based on Drivability using Supervised Machine Learning via OBD Interface,” Annual Conference of the IEEE Industrial Electronics Society, 2024.

  • D. Papaioannou, I.T. Christou, N. Anagnou, A. Chatziioannou, “ΑΛΓΟΡΙΘΜΟΙ ΒΑΘΙΑΣΜΑΘΗΣΗΣ (DEEP LEARNING) ΓΙΑ ΤΑΧΕΙΑ ΔΙΑΓΝΩΣΗ ΤΗΣ ΟΞΕΙΑΣ ΛΕΜΦΟΒΛΑΣΤΙΚΗΣΛΕΥΧΑΙΜΙΑΣ,” 35ο Πανελλήνιο Αιματολογικό Συνέδριο, 7-9 Νοε. 2024, Θεσ/νίκη, Ελλάς. Accepted as e-poster presentation.

  • S. Lavdas, D. Sklavounos, N. Bakas, P. Gkonis, V. Goltsi and P. Siaperas, “A machine learning implementation to multiple sclerosis signal conduction through nervous system for decision support,” 2023 2nd International Rehabilitation Conference, pp. 104-11.

  • S. Lavdas, D. Sklavounos, P. Gkonis, P. Siaperas, and N. Bakas, “Identification of Multiple Sclerosis Signals Dependence on Patients’ Medical Conditions Through Stochastic Perturbation of Features in Five Machine Learning Models”, 2023 19th European Mediterranean & Middle Eastern Conference on Information Systems (EMCIS) Conference, vol. 464, doi: https://doi.org/10.1007/978-3-031-30694-5_5.

  • S. Lavdas, Muhammad Tariq, Constantinos Papadias, “On the Analysis of EGaIn LiquidAntenna Array: Towards Enhanced Performance and Adaptability in Wireless Communication Systems,” In: 21st European Mediterranean & Middle Eastern Conference on Information Systems. Accepted July 2024. The proceedings will soon be available: https://link.springer.com/book/9783031564772

  • Nikolaos Bakas, Spyros Lavdas, Konstantinos Vavousis, Christos Christodoulou, Andreas Langousis. “Automated machine learning in a multi-agent environment.” In: 21st European Mediterranean & Middle Eastern Conference on Information Systems. Accepted July 2024. The proceedings will soon be available: https://link.springer.com/book/10.1007/978-3-031-56478-9.

  • Konstantopoulos, P. Desombre, G. A. Ropokis, and Y. Louët, “Filter Shape Index Modulation for single antenna Non-Orthogonal Multiple Access systems,” 2024 4th URSI Atlantic RadioScience Meeting (AT-RASC), Meloneras, Spain, 2024, pp. 1-4.

  • M. D. Avgerinou, V. Stefanou, A. Karampelas “A Tale of Three GenAI Assessments from High School, to Undergraduate and Graduate Classrooms.” In T. Bastiaens (Ed.), Proceedings of EdMedia + Innovate Learning (pp 147-156). Brussels, Belgium: Association for the Advancement of Computing in Education (AACE).Retrieved October 4, 2024, from www.learntechlib.org/primary/p/224516/

  • N.P. Bakas, M. Papadaki, E. Vagianou, I. Christou, & S.A. Chatzichristofis (2024). “Integrating LLMs in Higher Education, Through Interactive Problem Solving and Tutoring: Algorithmic Approach and Use Cases.” In M. Papadaki, M. Themistocleous, K. Al Marri, & M. Al Zarouni (Eds.), Information Systems. EMCIS 2023 (Lecture Notes in Business Information Processing, Vol. 501). Springer, Cham. https://doi.org/10.1007/978-3-031-56478-9_21

  • Konstantinos Papachristofis, Georgios Vardoulias, Konstantinos Vavousis.“Comparative Evaluation of Cybersecurity Maturity Models and Frameworks.” In 21st European Mediterranean & Middle Eastern Conference on Information Systems. Accepted July 2024. The proceedings will soon be available: https://link.springer.com/book/9783031564772

  • Vetsikas Ioannis, “The Importance of Studying Tabletop Games for Computer Game Design Courses,” In 21st European Mediterranean & Middle Eastern Conference on Information Systems. Accepted July 2024. The proceedings will soon be available: https://link.springer.com/book/9783031564772

  • Manios Andreas and Vetsikas Ioannis, “Smart List: A User-Based Collaborative Filtering System for Grocery List Creation,” In 21st European Mediterranean & Middle Eastern Conference on Information Systems. Accepted July 2024. The proceedings will soon be available: https://link.springer.com/book/9783031564772

  • N. Yuca, N. Matyunin, E. Arzoglou, N. A. Anagnostopoulos, and S. Katzenbeisser.”A Survey on Privacy-Preserving Computing in the Automotive Domain.” ACM Computing Surveys 57(2). (Submitted for Review). 2024.

  • K. Vergopoulos “Ship Engine Data Analysis for the Application of Machine Learning Algorithms,” 2023 8th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM), Nov 10, 2023.