Publications

2025

Pezoulas, V. C., Tachos, N. S., Zaridis, D. I., Chatzis, L., Goules, A., Marias, K., Tsiknakis, M., Tzioufas A. G., and Fotiadis, D.

A synthetic data-driven generation approach to enhance the fairness and privacy of AI-based systems in the domain of rare diseases

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IEEE BHI conference 2025

2025

Apostolidis, K., Zaridis, D. I., Tachos, N. S., Pezoulas, V. C., Marias, K., Tsiknakis, M., and Fotiadis, D

Adversarial Robustness Evaluation of Deep Learning Segmentation Models and Loss Functions in Prostate MRI

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Proceedings of the IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)

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2025

Seralidou, E.; Kioskli, K.; Fotis, T.; Polemi

AI_TAF: A Human-Centric Trustworthiness Risk Assessment Framework for AI Systems

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This paper presents the AI Trustworthiness Assessment Framework (AI_TAF), a comprehensive methodology for evaluating and mitigating trustworthiness risks across all stages of an AI system’s lifecycle. The framework accounts for the criticality of the system based on its intended application, the maturity level of the AI teams responsible for ensuring trust, and the organisation’s risk tolerance regarding trustworthiness. By integrating both technical safeguards and sociopsychological considerations, AI_TAF adopts a human-centric approach to risk management, supporting the development of trustworthy AI systems across diverse organisational contexts and at varying levels of human–AI maturity. Crucially, the framework underscores that achieving trust in AI requires a rigorous assessment and advancement of the trustworthiness maturity of the human actors involved in the AI lifecycle. Only through this human-centric enhancement can AI teams be adequately prepared to provide effective oversight of AI systems

Computers 2025, 14, 243.

https://doi.org/10.3390/computers14070243
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2025

Explanations for Trustworthy AI in Critical Infrastructure: A Case from Wastewater Treatment in Norway

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Position paper for the CHI 2025 workshop on Human-Centered Explainable AI - HCXAI 2025

Proceedings of the 2025 Workshop on Human-Centered Explainable AI @CHI: Human-Centered Explainable AI @CHI'25 (HCXAI), Yokohama, Japan, April 26-May 1, 2025, Page(s) 11 - 15

https://doi.org/10.5281/zenodo.15104919

2025

Kitty Kioskli, Elisavet Grigoriou, Shareeful Islam, Andrianos M. Yiorkas, Loizos Christofi & Haralambos Mouratidis

A risk and conformity assessment framework to ensure security and resilience of healthcare systems and medical supply chain

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Kioskli, K., Grigoriou, E., Islam, S. et al. A risk and conformity assessment framework to ensure security and resilience of healthcare systems and medical supply chain. Int. J. Inf. Secur. 24, 90 (2025). https://doi.org/10.1007/s10207-025-01009-z

Int. J. Inf. Secur. 24, 90 (2025)

https://doi.org/10.1007/s10207-025-01009-z
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2025

Kitty Kioskli ,Eleni Seralidou and Nineta Polemi

A Practical Human-Centric Risk Management (HRM) Methodology

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Various standards (e.g., ISO 27000x, ISO 31000:2018) and methodologies (e.g., NIST SP 800-53, NIST SP 800-37, NIST SP 800-161, ETSI TS 102 165-1, NISTIR 8286) are available for risk assessment. However, these standards often overlook the human element. Studies have shown that adversary profiles (AP), which detail the maturity of attackers, significantly affect vulnerability assessments […]

Electronics 2025, 14(3), 486;

https://doi.org/10.3390/electronics14030486
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2024

Eivind Bøhn , Sølve Eidnes , Kjell Rune Jonassen

Machine learning in wastewater treatment: insights from modelling a pilot denitrification reactor

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Wastewater treatment plants are increasingly recognized as promising candidates for machine learning applications, due to their societal importance and high availability of data. However, their varied designs, operational conditions, and influent characteristics hinder straightforward automation. In this study, we use data from a pilot reactor at the Veas treatment facility in Norway to explore how […]

arXiv:2412.14030v2, 2025

https://doi.org/10.48550/arXiv.2412.14030
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2024

Pezoulas, V. C., Zaridis, D. I., Mylona, E., Androutsos, C., Apostolidis, K., Tachos, N. S., and Fotiadis, D. I.

Synthetic data generation methods in healthcare: A review on open-source tools and methods

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Computational and Structural Biotechnology Journal, 23, 2892–2910.

https://doi.org/10.1016/j.csbj.2024.07.005
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2024

Evangelia Anagnostopoulou, Nikolaos Antonios Grammatikos, Dimitris Apostolou, Gregoris Mentzas

Trustworthy AI in education: A Roadmap for Ethical and Effective Implementation

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SETN '24: Proceedings of the 13th Hellenic Conference on Artificial Intelligence

https://doi.org/10.1145/3688671.368878
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2024

Leone GR, Carboni A, Moroni D, Colantonio S.

Transforming public transport through responsible AI: insight from the FAITH project

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ERCIM News, Chapter in a book

https://ercim-news.ercim.eu/en138/special/transforming-public-transport-through-responsible-ai-insight-from-the-faith-project