Journal Publications

2025

[5] He, Z., Stevens, A., Ouyang, C., De Smedt, J., Barros, A. J., Moreira, C. Crafting Imperceptible On-Manifold Adversarial Attacks for Tabular Data. Applied Soft Computing. (In review)

[4] Stevens, A., De Smedt, J., Peeperkorn, J., De Weerdt, J. Realistic Adversarial Examples for Business Processes using Variational Autoencoders. ACM Transactions on Knowledge Discovery from Data. (In review)

[3] Van Wallendael, L., Vanneste, L., Zhang, Y., Stevens, A., De Smedt, J. Mitigating downside risk: ESG Integration in Portfolio Construction with Stock Preselection Using Machine Learning and Mean-CVaR Optimization. Journal of International Financial Markets, Institutions & Money. (In review)

[2] Stevens, A., Ouyang, C., De Smedt, J., Moreira, C. Plausible and Feasible Counterfactuals for Predictive Process Monitoring. IEEE Transactions on Services Computing.

[1] Bertrand, Y., Stevens, A., Deforce, B., De Smedt, J., De Weerdt, J., Serral, E. Approaches for IoT-enhanced Predictive Process Monitoring. Process Science.

2024

[2] Reusens, M., Stevens, A., Tonglet, J., De Smedt, J., Verbeke, W., vanden Broucke, S., Baesens, B. Evaluating Text Classification: A Benchmark Study. Expert Systems with Applications.

2023

[1] Stevens, A., De Smedt, J. Explainability in Process Outcome Prediction: Guidelines to Obtain Interpretable and Faithful Models. European Journal on Operational Research.

Conference Proceedings

2023

[3] Stevens, A., Peeperkorn, J., De Smedt, J., De Weerdt, J. Manifold Learning for Adversarial Robustness in Predictive Process Monitoring. International Conference on Process Mining.

[2] Peeperkorn, J., Vázquez, C.O., Stevens, A., De Smedt, J., vanden Broucke, S., De Weerdt, J. Outcome-Oriented Predictive Process Monitoring on Positive and Unlabelled Event Logs. Machine Learning for Process Mining.

[1] Stevens, A., De Smedt, J., Peeperkorn, J. Quantifying Explainability in Outcome-Oriented Predictive Process Monitoring. Machine Learning for Process Mining.

2022

[2] Stevens, A., De Smedt, J., Peeperkorn, J., De Weerdt, J. Assessing the Robustness in Predictive Process Monitoring through Adversarial Attacks. International Conference on Process Mining.

2020

[1] Stevens, A., Deruyck, P., Van Veldhoven, Z., Vanthienen, J. Explainability and Fairness in Machine Learning: Improve Fair End-to-end Lending for Kiva. IEEE Symposium Series on Computational Intelligence (SSCI).

Academic Service

Journals Reviewed For

  • Data & Knowledge Engineering (2024)
  • Information Sciences (2023)
  • IEEE Transactions on Services Computing (2023)
  • Transactions on Knowledge Discovery from Data (2023)
  • Decision Support Systems (2023)

Conference Reviewing

  • International Conference on Process Mining (2024, 2022, 2021)
  • International Conference on Business Process Management (2023)
  • Conference on Advanced Information Systems Engineering (2024, 2023)
  • International Conference on Cooperative Information Systems (2023)

Invited Talks and Presentations

  • ELA Triangle AI Workshop (2024)
  • School of Information Systems, Queensland University of Technology (2023)
  • Belgian Operational Research Society (2024, 2023)
  • International Conference on Process Mining (2022)
  • Machine Learning for Process Mining (2021)
  • Various Research Seminars (2021-2024)

Guest Lectures

  • Network Analysis in Software Design and Programming II (Feb 2022)
  • Explainable Artificial Intelligence in Postgraduate Business Analytics (May 2024, March 2025)