prof.dr. M.I.A. Stoelinga (Mariëlle)


Over mij

Professor of Risk Management for High-tech systems

 How do we design our robots, nuclear plants, railway systems and heart monitors such that they are safe and reliable? How do we make sure that data centers and water supply systems are aways available?

I am developing quantitative risk assessments methods that ensure that the risks related to high tech systems lie within acceptable boundaries. I develop techniques to analyze, predict, improve reliability of complex systems, using fault trees, model-based testing, and architectural reliability modeling. 

Technically, distinguishing feature of my techniques is compositionality: I derive risk profiles from a complex systems from component risk profiles, using powerful techniques from model checking. This makes life easy, flexible and fast. 

Further, I am the scientific programme leaders of the executive MSc programme on Risk Management. This is a 70 EC Master programme for professionals. 

I also hold a 0.2 appointment as a full professor at the Radboud University Nijmegen.


Engineering & Materials Science
Fault Tree Analysis
Formal Methods
Intelligent Buildings
Model Checking
Statistical Models
Fault Tree
Fault Tree Analysis


  • Schouten & Nelissen University of Applied Sciences
    Advisory panel of the Master on Quality Management at Schouten & Nelissen University of Applied Sciences
  • Nyenrode Business University
    Advisory board Executive Insurance Program


Budde, C. E. , Jansen, D., Locht, I. , & Stoelinga, M. (2022). Learning to Learn HVAC Failures: Layering ML Experiments in the Absence of Ground Truth. In Reliability, Safety, and Security of Railway Systems. Modelling, Analysis, Verification, and Certification: 4th International Conference, RSSRail 2022, Paris, France, June 1–2, 2022, Proceedings (pp. 95-111). (Lecture notes in computer science; Vol. 13294). Springer. https://doi.org/10.1007/978-3-031-05814-1_7
Badings, T. S., Jansen, N., Junges, S. , Stoelinga, M. I. A. , & Volk, M. (2022). Sampling-Based Verification of CTMCs with Uncertain Rates. arXiv.org. https://arxiv.org/abs/2205.08300
Basgöze, D. , Volk, M. , Katoen, J-P., Khan, S. , & Stoelinga, M. (2022). BDDs Strike Back: Efficient Analysis of Static and Dynamic Fault Trees. In NASA Formal Method: 14th International Symposium, NFM 2022, Pasadena, CA, USA, May 24–27, 2022, Proceedings (pp. 713-732). [Chapter 38] (Lecture notes in computer science; Vol. 13260). Springer. https://doi.org/10.1007/978-3-031-06773-0_38
Budde, C. E. , Kolb, C. , & Stoelinga, M. (2021). Attack Trees vs. Fault Trees: Two Sides of the Same Coin from Different Currencies. In A. Abate, & A. Marin (Eds.), Quantitative Evaluation of Systems: 18th International Conference, QEST 2021, Proceedings (pp. 457-467). (Lecture Notes in Computer Science; Vol. 12846). Springer. https://doi.org/10.1007/978-3-030-85172-9_24
Stoelinga, M. I. A. , Kolb, C. , Nicoletti, S. M. , Budde, C. E. , & Hahn, E. M. (2021). The Marriage Between Safety and Cybersecurity: Still Practicing. In A. Laarman, & A. Sokolova (Eds.), Model Checking Software. SPIN 2021: 27th International Symposium, SPIN 2021, Virtual Event, July 12, 2021, Proceedings (pp. 3-21). (Lecture Notes in Computer Science; Vol. 12864). Springer. https://doi.org/10.1007/978-3-030-84629-9_1
Jimenez-Roa, L. A., Heskes, T. , Tinga, T. , & Stoelinga, M. I. A. (2021). Automatic inference of fault tree models via multi-objective evolutionary algorithms. Manuscript submitted for publication.
Jimenez-Roa, L. A., Heskes, T. , & Stoelinga, M. (2021). Fault Trees, Decision Trees, and Binary Decision Diagrams: A systematic comparison. In B. Castanier, M. Cepin, D. Bigaud, & C. Bérenguer (Eds.), Proceedings of the 31st European Safety and Reliability Conference (ESREL 2021) (pp. 673-680). Research Publishing. https://doi.org/10.3850/978-981-18-2016-8_241-cd
Bouwman, M. , van der Wal, D., Luttik, B. , Stoelinga, M. , & Rensink, A. (2020). What is the point: Formal analysis and test generation for a railway standard. In P. Baraldi, F. Di Maio, & E. Zio (Eds.), Proceedings of the 30th European Safety and Reliability Conference and the 15th Probabilistic Safety Assessment and Management Conference (pp. 921-928). Research Publishing Services. https://doi.org/10.3850/978-981-14-8593-0_4410-cd
Arias, J. , Budde, C. E., Penczek, W. , Petrucci, L., Sidoruk, T. , & Stoelinga, M. (2020). Hackers vs. Security: Attack-Defence Trees as Asynchronous Multi-agent Systems. In S-W. Lin, Z. Hou, & B. Mahoney (Eds.), Formal Methods and Software Engineering - 22nd International Conference on Formal Engineering Methods, ICFEM 2020, Proceedings (pp. 3-19). (Lecture Notes in Computer Science; Vol. 12531). Springer. https://doi.org/10.1007/978-3-030-63406-3_1
Budde, C. E. , & Stoelinga, M. (2020). Automated Rare Event Simulation for Fault Tree Analysis via Minimal Cut Sets. In H. Hermanns (Ed.), Measurement, Modelling and Evaluation of Computing Systems - 20th International GI/ITG Conference, MMB 2020, Proceedings (pp. 259-277). (Lecture Notes in Computer Science; Vol. 12040). Springer. https://doi.org/10.1007/978-3-030-43024-5_16
Budde, C. E. , Biagi, M. , Monti, R. E., D’Argenio, P. R. , & Stoelinga, M. (2020). Rare Event Simulation for Non-Markovian Repairable Fault Trees. In A. Biere, & D. Parker (Eds.), Tools and Algorithms for the Construction and Analysis of Systems: 26th International Conference, TACAS 2020, Held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2020, Dublin, Ireland, April 25–30, 2020, Proceedings (Vol. I, pp. 463-482). (Lecture Notes in Computer Science; Vol. 12078). Springer. https://doi.org/10.1007/978-3-030-45190-5_26
Budde, C. E. , Ruijters, E. , & Stoelinga, M. (2020). The Dynamic Fault Tree Rare Event Simulator. In M. Gribaudo, D. N. Jansen, & A. Remke (Eds.), Quantitative Evaluation of Systems: 17th International Conference, QEST 2020, Vienna, Austria, August 31 – September 3, 2020, Proceedings (pp. 233-238). (Lecture Notes in Computer Science; Vol. 12289), (Theoretical Computer Science and General Issues). Springer. https://doi.org/10.1007/978-3-030-59854-9_17
Ton, B. , Basten, R., Bolte, J. , Braaksma, J., Bucchianico, A. D., Calseyde, P. V. D., Grooteman, F., Heskes, T., Jansen, N., Teeuw, W. , Tinga, T. , & Stoelinga, M. (2020). PrimaVera: Synergising Predictive Maintenance. Applied Sciences, 10(23), 1-19. [8348]. https://doi.org/10.3390/app10238348
van Huizen, J. C. , Huisman, M. , Lathouwers, S. A. M. , Schaafstal, A. M. , & Stoelinga, M. I. A. (2020). Alice and Eve: a celebration of women in computer science. In J. van der Veen, N. van Hattum-Janssen, H-M. Järvinen, T. de Laet, & I. ten Dam (Eds.), Engaging, Engineering, Education: Book of Abstracts, SEFI 48th Annual Conference University of Twente (online), 20-24 September, 2020 University of Twente.
Linard, A., Bueno, M. , Bucur, D. , & Stoelinga, M. I. A. (2019). Induction of Fault Trees through Bayesian Networks. In M. Beer, & E. Zio (Eds.), Proceedings of the 29th European Safety and Reliability Conference (ESREL) (pp. 910-918). Research Publishing. http://itekcmsonline.com/rps2prod/esrel2019/e-proceedings/pdf/0596.pdf
Kließ, M. S. , Stoelinga, M. , & van Riemsdijk, M. B. (2019). From Good Intentions to Behaviour Change: Probabilistic Feature Diagrams for Behaviour Support Agents. In M. Baldoni, M. Dastani, B. Liao, Y. Sakurai, & R. Zalila-Wenkstern (Eds.), PRIMA 2019: Principles and Practice of Multi-Agent Systems: 22nd International Conference, Turin, Italy, October 28-31, 2019, Proceedings (pp. 354-369). (Lecture Notes in Computer Science; Vol. 11873). Springer. https://doi.org/10.1007/978-3-030-33792-6_22
André, É., Lime, D., Ramparison, M. , & Stoelinga, M. (2019). Parametric Analyses of Attack-Fault Trees. In Proceedings - 2019 19th International Conference on Application of Concurrency to System Design, ACSD 2019 (pp. 33-42). (Proceedings - International Conference on Application of Concurrency to System Design, ACSD; Vol. 2019). IEEE. https://doi.org/10.1109/ACSD.2019.00008
Linard, A. , Bucur, D. , & Stoelinga, M. (2019). Fault Trees from Data: Efficient Learning with an Evolutionary Algorithm. In N. Guan, J-P. Katoen, & J. Sun (Eds.), Dependable Software Engineering. Theories, Tools, and Applications: 5th International Symposium, SETTA 2019, Shanghai, China, November 27-29, 2019, Proceedings (pp. 19-37). (Lecture Notes in Computer Science; Vol. 11951), (Programming and Software Engineering). Springer. https://doi.org/10.1007/978-3-030-35540-1_2
Nakhaee, M. C. , Hiemstra, D. , Stoelinga, M., & Noort, M. V. (2019). The Recent Applications of Machine Learning in Rail Track Maintenance: A Survey. In S. Collart-Dutilleul, T. Lecomte, & A. B. Romanovsky (Eds.), Reliability, Safety, and Security of Railway Systems. Modelling, Analysis, Verification, and Certification: Third International Conference, RSSRail 2019, Lille, France, June 4-6, 2019, Proceedings (pp. 91-105). (Lecture Notes in Computer Science; Vol. 11495). Springer. https://doi.org/10.1007/978-3-030-18744-6_6

Pure Link

Google Scholar Link

Verbonden aan Opleidingen


Vakken Collegejaar  2021/2022

Vakken in het huidig collegejaar worden toegevoegd op het moment dat zij definitief zijn in het Osiris systeem. Daarom kan het zijn dat de lijst nog niet compleet is voor het gehele collegejaar.

Vakken Collegejaar  2020/2021



Universiteit Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling (gebouwnr. 11), kamer 3063
Hallenweg 19
7522NH  Enschede

Navigeer naar locatie


Universiteit Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling  3063
Postbus 217
7500 AE Enschede

Social Media