Stefan Brunner

Projects

• Verification and Validation Framework for Safe Railway AI Systems Across Their Lifecycle / Team member / ongoing
• certAInty – A Certification Scheme for AI systems / Team member / completed
• Machine Protection and Autonomous Predictive Interlock System / Team member / completed

Publications

Written conference contributions, peer-reviewed

• Frischknecht-Gruber, C., Denzel, P., Reif, M., Billeter, Y., Brunner, S., Forster, O., Schilling, F.-P., Weng, J., & Chavarriaga, R. (2025). AI assessment in practice : implementing a certification scheme for AI trustworthiness [Conference paper]. In R. Görge, E. Haedecke, M. Poretschkin, & A. Schmitz (Eds.), Symposium on Scaling AI Assessments (SAIA 2024) (pp. 15:1–15:18). Schloss Dagstuhl – Leibniz-Zentrum für Informatik. https://doi.org/10.4230/OASIcs.SAIA.2024.15
• Billeter, Y., Denzel, P., Chavarriaga, R., Forster, O., Schilling, F.-P., Brunner, S., Frischknecht-Gruber, C., Reif, M. U., & Weng, J. (2024). MLOps as enabler of trustworthy AI [Conference paper]. 2024 11th IEEE Swiss Conference on Data Science (SDS), 37–40. https://doi.org/10.1109/SDS60720.2024.00013
• Denzel, P., Brunner, S., Billeter, Y., Forster, O., Frischknecht-Gruber, C., Reif, M. U., Schilling, F.-P., Weng, J., Chavarriaga, R., Amini, A., Repetto, M., & Iranfar, A. (2024). Towards the certification of AI-based systems [Conference paper]. 2024 11th IEEE Swiss Conference on Data Science (SDS), 84–91. https://doi.org/10.1109/SDS60720.2024.00020
• Brunner, S., Reif, M. U., & Senn, C. (2024). Deep Ensemble Novelty Detection : novelty detection and fault identification in multivariate data [Conference paper]. In XS. Yang, S. Sherratt, N. Dey, & A. Joshi (Eds.), Proceedings of Ninth International Congress on Information and Communication Technology (pp. 443–461). Springer. https://doi.org/10.1007/978-981-97-3302-6_36
• Weng, J., Denzel, P., Reif, M. U., Schilling, F.-P., Billeter, Y., Frischknecht-Gruber, C., Brunner, S., Chavarriaga, R., Repetto, M., & Iranfar, A. (2024, June). Certification scheme for artificial intelligence based systems. 34th European Safety and Reliability Conference (ESREL), Cracow, Poland, 23-27 June 2024. https://doi.org/10.21256/zhaw-30549
• Brunner, S., Reif, M. U., & Rejzek, M. (2024). Improving resilience and robustness in artificial intelligence systems through adversarial training and verification [Conference paper]. In K. Kołowrocki & E. Dąbrowska (Eds.), Advances in Reliability, Safety and Security, Part 4 (pp. 39–48). Polish Safety and Reliability Association. https://doi.org/10.21256/zhaw-30985
• Brunner, S., Frischknecht-Gruber, C., Reif, M. U., & Weng, J. (2023). A comprehensive framework for ensuring the trustworthiness of AI systems [Conference paper]. In M. P. Brito, T. Aven, P. Baraldi, M. Čepin, & E. Zio (Eds.), Proceeding of the 33rd European Safety and Reliability Conference (pp. 2772–2779). Research Publishing. https://doi.org/10.3850/978-981-18-8071-1_P230-cd
• Brunner, S., Frischknecht-Gruber, C., Reif, M. U., & Senn, C. (2022). Deep Gaussian mixture model : a novelty detection method for time series [Conference paper]. In M. C. Leva, E. Patelli, L. Podofillini, & S. Wilson (Eds.), Proceedings of the 32nd European Safety and Reliability Conference (pp. 1291–1298). Research Publishing. https://doi.org/10.3850/978-981-18-5183-4_R22-12-325-cd

Oral conference contributions and abstracts

• Brunner, S., Reif, M. U., & Rejzek, M. (2025, January 29). Increasing trust in medical AI systems through systematic verification : a framework for developing and verification of responsible AI. AI Days @ HES-SO, Geneva and Lausanne, Switzerland, 27–29 January 2025.
• Denzel, P., Brunner, S., Luley, P.-P., Frischknecht-Gruber, C., Reif, M. U., Schilling, F.-P., Amini, A., Repetto, M., Iranfar, A., Weng, J., & Chavarriaga, R. (2023, November 2). A framework for assessing and certifying explainability of health-oriented AI systems. Explainable AI in Medicine Workshop, Lugano, Switzerland, 2-3 November 2023.

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