My research focuses on the design and development of probabilistic decision support systems for safety-critical industrial environments, with a particular emphasis on control room operations. I use Bayesian networks and related probabilistic graphical models to build interpretable, data-driven tools that assist human operators in complex monitoring, alarm management, and fault diagnosis tasks.

As a member of the Centre for Human Factors in Safety and Sustainability (HFISS) at TU Dublin, my work integrates human-centred design principles and human-in-the-loop validation to ensure that models are not only statistically rigorous but practically usable by real operators in high-stakes settings. This includes the design of experimental studies, including simulator-based trials, to evaluate operator performance and system effectiveness under realistic conditions.

A central ambition of my research is to bridge the gap between academic modelling and industrial application. I actively pursue collaborative partnerships with industry to translate probabilistic AI methods into deployable, trustworthy tools that meet the reliability and interpretability demands of safety-critical practice.

Journal Papers

1. Mietkiewicz, J., Abbas, A. N., Amazu, C. W., Baldissone, G., Madsen, A. L., Demichela, M., & Leva, M. C. (2024). Enhancing control room operator decision making. Processes, 12(2), 328. https://doi.org/10.3390/pr12020328
2. Amazu, C. W., Mietkiewicz, J., Abbas, A. N., Briwa, H., Alonso-Perez, A., Baldissone, G., Fissore, D., Demichela, M., & Leva, M. C. (2024). Exploring the influence of human system interfaces: Introducing support tools and an experimental study. International Journal of Human–Computer Interaction, 1–18. https://doi.org/10.1080/10447318.2024.2376354
3. Amazu, C. W., Mietkiewicz, J., Abbas, A. N., Baldissone, G., Fissore, D., Demichela, M., Madsen, A. L., & Leva, M. C. (2026). Managing the unexpected: Operator behavioural data and its value in predicting correct alarm responses. Reliability Engineering & System Safety. https://doi.org/10.1016/j.ress.2026.112616
4. Abbas, A. N., Amazu, C. W., Mietkiewicz, J., Briwa, H., Alonso Perez, A., Baldissone, G., Demichela, M., Chasparis, G. C., Kelleher, J. D., & Leva, M. C. (2024). Analyzing operator states and the impact of AI-enhanced decision support in control rooms: A human-in-the-loop specialized reinforcement learning framework for intervention strategies. International Journal of Human–Computer Interaction, 1–35. https://doi.org/10.1080/10447318.2024.2391605
5. Amazu, C. W., Mietkiewicz, J., Abbas, A. N., Briwa, H., Alonso Perez, A., Baldissone, G., Demichela, M., Fissore, D., Madsen, A. L., & Leva, M. C. (2024). Experiment data: Human-in-the-loop decision support in process control rooms. Data in Brief, 53, 110170. https://doi.org/10.1016/j.dib.2024.110170
6. Castro Rodriguez, D. J., Mietkiewicz, J., Vitale, M., Baldissone, G., Barresi, A. A., & Demichela, M. (2024). NaTech triggered by lightning: Novel insights from past events in the process industry. Heliyon, 10(11). https://doi.org/10.1016/j.heliyon.2024.e31610

Conference Papers

1. Mietkiewicz, J., & Madsen, A. L. (2023). Enhancing control room operator decision making: An application of dynamic influence diagrams in formaldehyde manufacturing. In European Conference on Symbolic and Quantitative Approaches with Uncertainty (pp. 15–26). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-45608-4_2
2. Mietkiewicz, J., Abbas, A. N., Amazu, C. W., Madsen, A. L., & Baldissone, G. (2023). Dynamic influence diagram-based deep reinforcement learning framework and application for decision support for operators in control rooms. In Proceedings of the 33rd European Safety and Reliability Conference (ESREL 2023) (pp. 2806–2813). Research Publishing. https://doi.org/10.3850/978-981-18-8071-1_p531-cd
3. Mietkiewicz, J., & Madsen, A. L. (2022). Data driven Bayesian network to predict critical alarm. In Proceedings of the 32nd European Safety and Reliability Conference (ESREL 2022) (p. 522). Research Publishing. https://doi.org/10.3850/978-981-18-5183-4_s33-06-643-cd
   Mietkiewicz, J., & Madsen, A. L. (2022). Improvement of the fine tuning algorithm. In BNAIC/BeNeLearn 2022. https://doi.org/10.21427/7kqm-cq71
4. Amazu, C. W., Mietkiewicz, J., Abbas, A. N., Baldissone, G., Demichela, M., Fissore, D., & Leva, M. C. (2024). Lessons learnt from human-in-loop experimental scenarios for advanced automation in process safety. In Advances in Reliability, Safety and Security — Part 5: Human Factors in System Reliability, Safety and Security (Vol. 5, pp. 9–18). Polish Safety and Reliability Association.
5. Mietkiewicz, J., Abbas, A. N., Amazu, C. W., Madsen, A. L., & Leva, M. C. (2025). Physiological impact assessment of decision support systems on control room operators: An ANCOVA analysis. In Proceedings of the 35th European Safety and Reliability & 33rd Society for Risk Analysis Europe Conference (pp. 1765–1772). Research Publishing. https://doi.org/10.3850/978-981-94-3281-3_ESREL-SRA-E2025-P9407-cd
6. Ari Ajeni, Mietkiewicz, J., Leva, M. C., D'Arcy, L., & Kinahan, M. (2022). Women's perspective of personal safety on public transport in Ireland. In Proceedings of the 32nd European Safety and Reliability Conference (ESREL 2022). Research Publishing. https://doi.org/10.3850/978-981-18-5183-4_s06-15-565-cd

Datasets

1. Amazu, C. W., Mietkiewicz, J., Abbas, A. N., Briwa, H., Alonso Perez, A., Baldissone, G., Demichela, M., Fissore, D., & Madsen, A. L. (2024). Experiment Data: Human-in-the-Loop Decision Support in Process Control. Zenodo, 2024,. https://zenodo.org/records/10600674