Publications

2026

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

An Empirical Study of Assessing and Mitigating Trustworthiness of Educational AI

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This paper examines how researchers checked the risks of an AI platform used for STEM learning in real secondary-school classrooms. It covers a learning companion, a tool that classifies student performance, and a system that recommends learning activities. After safeguards were introduced, results included 96.7% accuracy in classifying previously unseen students and an initial 80% teacher acceptance rate for recommendations.

https://sites.google.com/view/trust-ai-2026/home?authuser=0

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2026

Z. Uddin, S. Eidnes and K. R. Jonassen

A Transformer-Based Approach for Nitrate Concentration Estimation in a Pilot-Scale Denitrification Reactor

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In: 21st Annual System of Systems Engineering Conference (SoSE), Kongsberg, Norway, 2026, pp. 1-8,

https://doi.org/10.1109/SoSE69681.2026.11622386
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2025

Maglaras, L., Kioskli, K.

End-to-End Encryption: Technological and Human Factor Perspectives

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In: Schmorrow, D.D., Fidopiastis, C.M. (eds) Augmented Cognition. HCII 2025. Lecture Notes in Computer Science(), vol 15778. Springer, Cham.

https://doi.org/10.1007/978-3-031-93724-8_10

2025

Topini, Alberto & Cecchi, Lorenzo & Fedi, Fausto & Minarelli, Marco & Bucci, Alessandro & Ridolfi, Alessandro

Trustworthy AI-Driven Autonomous Underwater Vehicles for Port Infrastructure Inspection: Paradigm Conceptualization

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Topini, Alberto & Cecchi, Lorenzo & Fedi, Fausto & Minarelli, Marco & Bucci, Alessandro & Ridolfi, Alessandro. (2025). Trustworthy AI-Driven Autonomous Underwater Vehicles for Port Infrastructure Inspection: Paradigm Conceptualization. 515-520. 10.1109/MetroSea66681.2025.11245714.

2025 IEEE International Workshop on Metrology for the Sea; Learning to Measure Sea Health Parameters (MetroSea)

https://10.1109/MetroSea66681.2025.11245714
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2025

Dr Theofanis Fotis , Kitty Kioskli, Eleni Seralidou

Charting Trustworthiness: A Socio-Technical Perspective on AI and Human Factors

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Integrating AI into critical decision-making environments, including cybersecurity, highlights the importance of understanding human factors in fostering trust and ensuring safe human-AI collaboration. Existing research emphasizes that personality traits, such as openness, trust propensity, and affinity for technology, significantly influence user interaction with AI systems, impacting trustworthiness and reliance behaviours. Furthermore, studies in cybersecurity underscore […]

Human Factors in Cybersecurity. AHFE (2025) International Conference. AHFE Open Access, vol 168. AHFE International, USA

http://doi.org/10.54941/ahfe1006137
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2025

Andrea Berti, Rossana Buongiorno, Gianluca Carloni, Claudia Caudai , Francesco Conti, Giulio Del Corso , Danila Germanese , Davide Moroni, Eva Pachetti , Maria Antonietta Pascali and Sara Colantonio

From Covid-19 detection to cancer grading: how medical-AI is boosting clinical diagnostics and may improve treatment

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The integration of artificial intelligence (AI) into medical imaging has guided an era of transformation in healthcare. This paper presents the research activities that a multidisciplinary research group within the Signals and Images Lab of the Institute of Information Science and Technologies of the National Research Council of Italy is carrying out to explore the great potential of AI in medical imaging. From the convolutional neural network-based segmentation of Covid-19 lung patterns to the radiomic signature for benign/malignant breast nodule discrimination, to the automatic grading of prostate cancer, this work highlights the paradigm shift that AI has brought to medical imaging, revolutionizing diagnosis and patient care.

In Ital-IA 2023: 3rd National Conference on Artificial Intelligence, CINI (pp. 372–377). CEUR Workshop Proceedings.

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2025

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

Towards Trustworthy AI in STEM Education: Challenges and Strategies from the Trust-AI Platform

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In Proceedings of TRUST-AI 2025 – The European Workshop on Trustworthy AI, edited by Asbjørn Følstad et al., 103–111. CEUR Workshop Proceedings

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2025

Kitty Kioskli, Theofanis Fotis, Eleni Seralidou, Marios Passaris and Nineta Polemi

trustSense: Measuring Human Oversight Maturity for Trustworthy AI

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The integration of Artificial Intelligence (AI) systems into critical decision-making processes necessitates robust mechanisms to ensure trustworthiness, ethical compliance, and human oversight.

Computers 2025, 14(11), 483;

https://doi.org/10.3390/computers14110483
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2025

G. Del Corso, S. Colantonio, C. Caudai

Shedding light on uncertainties in machine learning: formal derivation and optimal model selection

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Journal of the Franklin Institute 362(2–3):107548,

https://doi.org/10.1016/j.jfranklin.2025.107548
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2025

E. Karampotsis, K. Kioskli, A. Tsirimpa, G. Dounias & A. Polydoropoulou

Understanding evacuation behavior for effective disaster preparedness: a hybrid machine learning approach

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Nat Hazards 120, 13627–13665 (2024)

https://doi.org/10.1007/s11069-024-06759-y
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