Prof. dr. S.I. (Ilker) Birbil
Hoogleraar AI & Optimization Techniques for Business & Society
Faculteit Economie en Bedrijfskunde
Sectie Business Analytics
Bezoekadres
- Plantage Muidergracht 12
Postadres
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Postbus 15953
1001 NL Amsterdam
Contactgegevens
Social media
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Publicaties
- refereed (26)
- wetenschappelijk (4)
- erkenning (16)
- supervised theses (1)
- working papers / preprints (2)
- datasets (1)
2026
- Kurtz, J., Birbil, Ş. İ., & den Hertog, D. (2026). Counterfactual explanations for linear optimization. European Journal of Operational Research, 329(1), 24-41. Advance online publication. https://doi.org/10.1016/j.ejor.2025.06.016
2025
- Boon, C. T., Durak, E., & Birbil, S. I. (2025). Towards a better understanding of misfit through explainable AI techniques. In J. Billsberry, & D. L. Talbot (Eds.), Employee Misfit (1 ed., Vol. 1, pp. 223–245). Springer. https://doi.org/10.1007/978-981-96-8208-9_12
- Cinà, G., Röber, T. E., Goedhart, R., & Birbil, Ş. İ. (2025). Why we do need explainable AI for healthcare. Diagnostic and Prognostic Research, 9, Article 24. https://doi.org/10.1186/s41512-025-00209-4
- Kuipers, M. F., Konus, U., Brundel, B. J. J. M., & Birbil, S. I. (2025). Communication strategies driving online health community patient awareness and engagement investigated within atrial fibrillation context. npj digital medicine, 8, Article 446. https://doi.org/10.1038/s41746-025-01854-1
- Maragno, D., Wiberg, H., Bertsimas, D., Birbil, S. I., den Hertog, D., & Fajemisin, A. O. (2025). Mixed-Integer Optimization with Constraint Learning. Operations Research, 73(2), 1011-1028. https://doi.org/10.1287/opre.2021.0707
- Mohammadi, A., Schoonhoven, M., Vogels, L. F. O., & Birbil, S. I. (2025). Scalable Bayesian Structure Learning for Gaussian Graphical Models Using Marginal Pseudo-Likelihood. Bayesian Analysis, 1. Advance online publication. https://doi.org/10.1214/25-BA1561
- Otto, D., Kurtz, J., & Birbil, S. I. (2025). Coherent Local Explanations for Mathematical Optimization. Manuscript submitted for publication.
- Röber, T. E., Goedhart, R., & Birbil, S. I. (2025). Clinicians’ Voice: Fundamental Considerations for XAI in Healthcare. In Proceedings of the 10th Machine Learning for Healthcare Conference: Proceedings of Machine Learning Research (PMLR) (Vol. 298) https://proceedings.mlr.press/v298/rober25a.html
- Röber, T. E., Lumadjeng, A., Akyuz, H., & Birbil, S. I. (2025). Rule Generation for Classification: Scalability, Interpretability, and Fairness. Computers & Operations Research, 183, Article 107163. https://doi.org/10.1016/j.cor.2025.107163
- Vogels, L., Mohammadi, R., Schoonhoven, M., Birbil, Ş. I., Dyrba, M., & Alzheimer's Disease Neuroimaging Initiative (2025). Modeling Alzheimer’s disease: Bayesian copula graphical model from demographic, cognitive, and neuroimaging data. Journal of Alzheimer's Disease, 108(1,supplement), S244-S257. https://doi.org/10.1177/13872877251337944
- Wasserkrug, S., Boussioux, L., den Hertog, D., Mirzazadeh, F., Birbil, S. I., Kurtz, J., & Maragno, D. (2025). Enhancing decision making through the integration of large language models and operations research optimization. In Proceedings of the 39th Annual AAAI Conference on Artificial Intelligence (27 ed., Vol. 39, pp. 28643-28650). (Proceedings of the AAAI Conference on Artificial Intelligence). https://doi.org/10.1609/aaai.v39i27.35090
- von Stackelberg, P. B., Goedhart, R., Huberts, L. C. E., Lokkerbol, J., & Birbil, S. I. (2025). Prediction of Depression Relapse Using Machine Learning With Administrative Data: Balancing Complexity and Simplicity. Quality and Reliability Engineering International. Advance online publication. https://doi.org/10.1002/qre.70139
2024
Birbil, İ., Martin, Ö., Onay, G., & Öztoprak, F. (2024). Bolstering stochastic gradient descent with model building. TOP, 32(3), 517-536. https://doi.org/10.1007/s11750-024-00673-z [details]- Julien, E., Postek, K., & Birbil, S. I. (2024). Machine Learning for K-adaptability in Two-Stage Robust Optimization. INFORMS Journal on Computing, 503.
- Maragno, D., Buti, G., Birbil, S. I., Liao, Z., Bortfeld, T., den Hertog, D., & Ajdari, A. (2024). Embedding machine learning based toxicity models within radiotherapy treatment plan optimization. Physics in Medicine and Biology, 69(7), Article 075003. https://doi.org/10.1088/1361-6560/ad2d7e [details]
- Maragno, D., Kurtz, J., Röber, T. E., Goedhart, R., Birbil, Ş. İ., & den Hertog, D. (2024). Finding regions of counterfactual explanations via robust optimization. INFORMS Journal on Computing, 36(5), 1316–1334. https://doi.org/10.1287/ijoc.2023.0153 [details]
- Vogels, L., Mohammadi, R., Schoonhoven, M., & Birbil, S. I. (2024). Bayesian Structure Learning in Undirected Gaussian Graphical Models: Literature Review with Empirical Comparison. Journal of the American Statistical Association, 119(548), 3164-3182. https://doi.org/10.1080/01621459.2024.2395504 [details]
- von Stackelberg, P., Goedhart, R., Birbil, S. I., & Does, R. J. M. M. (2024). Comparison of threshold tuning methods for predictive monitoring. Quality and Reliability Engineering International, 40(1), 499-512. https://doi.org/10.1002/qre.3436 [details]
2023
- Cina, G., Röber, T. E., Goedhart, R., & Birbil, S. I. (2023). Semantic match: Debugging feature attribution methods in XAI for healthcare. Proceedings of Machine Learning Research, 209, 182-191. https://proceedings.mlr.press/v209/cina23a.html [details]
- Karaca, U., Birbil, S. I., Aydin, N., & Mullaoğlu, G. (2023). Masking Primal and Dual Models for Data Privacy in Network Revenue Management. European Journal of Operational Research, 308(2), 818-831. https://doi.org/10.1016/j.ejor.2022.11.025 [details]
2022
- Birbil, S. I., Yildirim, S., Çopur, S., & Akyuz, M. H. (2022). Learning with Subset Stacking. Manuscript submitted for publication.
- Dekker, R., Koot, P., Birbil, S. I., & van Embden Andres, M. (2022). Co-designing Algorithms for Governance: Ensuring Responsible and Accountable Algorithmic Management of Refugee Camp Supplies. Big Data & Society, 9(1). https://doi.org/10.1177/20539517221087855 [details]
- Karaca, U., Birbil, S. I., Yildirim, S., & Aydin, N. (2022). Differentially Private Linear Optimization for Multi-party Resource Sharing. Manuscript submitted for publication.
- Kuru, N., Birbil, S. I., Gurbuzbalaban, M., & Yildirim, S. (2022). Differentially Private Accelerated Optimization Algorithms. SIAM Journal on Optimization, 32(2), 795-821. https://doi.org/10.1137/20M1355847 [details]
- Maragno, D., Röber, T. E., & Birbil, S. İ. (2022). Counterfactual Explanations Using Optimization With Constraint Learning. In OPT2022: Optimization for Machine Learning. Accepted papers OPT-ML. https://doi.org/10.48550/arXiv.2209.10997 [details]
2012
- Topaloglu, H., Ilker Birbil, S., Frenk, J. B. G., & Noyan, N. (2012). Tractable open loop policies for joint overbooking and capacity control over a single flight leg with multiple fare classes. Transportation Science, 46(4), 460-481. https://doi.org/10.1287/trsc.1110.0403
2025
- Engelhardt, F., Kurtz, J., Birbil, S. I., & Ralphs, T. (2025). Counterfactual Explanations for Integer Optimization Problems. Manuscript submitted for publication.
2022
- Cina, G., Röber, T., Goedhart, R., & Birbil, I. (2022). Why we do need Explainable AI for Healthcare. (v1 ed.) ArXiv. https://doi.org/10.48550/arXiv.2206.15363 [details]
2021
- Birbil, S. I. (Author), & Martin, O. (Author). (2021). Stochastic Model Building: SMB. Software, GitHub.
- Birbil, S. I. (Author). (2021). Learning with Subset Stacking: LESS. Software, GitHub.
Lidmaatschap / relevante positie
- Birbil, S. . (2021). Optimization and Machine Learning Group (LNMB). https://www.lnmb.nl/pages/dutchorgroups/proj10b.htm
- Birbil, S. . (2021). Optimisation for and with Machine Learning (OPTIMAL). https://optimal.uva.nl
Spreker
- Birbil, S. . (keynote speaker) (28-4-2022). IPD2022: Innovative Product Development International Conference, Kasetsart University. https://easychair.org/cfp/IPD2022
- Birbil, S. . (invited speaker) (12-4-2022). Data Science in Finance Conference - 2022, ABN AMRO. https://dsfc.nl/schedule-2022/
- Birbil, S. . (keynote speaker) (7-3-2022). 12th Annual International Conference on Industrial Engineering and Operations Management, Kadir Has University, Istanbul, Turkey.. https://ieomsociety.org/istanbul2022/
- Birbil, S. . (speaker) (29-9-2021). Optimization and Machine Learning: Overview and Current Research, Machine Learning for Optimization. https://video.uva.nl/media/Lecture+3.1/0_3cm8tcfl
- Birbil, S. . (speaker) (24-6-2021). Yapay Öğrenmede Yorumlanabilirlik, Sabanci University - Academy of Science: Machine Learning Summer School 2021. https://www.youtube.com/watch?v=83HHZ5INDx0
- Birbil, S. . (speaker) (11-1-2021). Rule Generation for Learning and Interpretation, Machine Learning NeEDS Mathematical Optimization. https://www.youtube.com/watch?v=ekcQEYd9C88
Andere
- Birbil, S. . (organiser), Romero Morales, D. (organiser), Rudin, C. (organiser), Fokkema, D. (organiser) & Akyuz, H. (participant) (17-10-2022 - 21-10-2022). Making Sense of Interpretable Machine Learning, Leiden (organising a conference, workshop, ...).
- Birbil, S. . (examiner) (7-9-2022). Molding the Symbiosis Between Human and Machine (examination).
- Birbil, S. . (examiner) (6-4-2022). Numerical Optimal Control of Open Channel Networks (examination).
- Birbil, S. . (organiser) & Martin, O. (organiser) (26-3-2022 - 27-3-2022). Stochastic Optimization for Large-Scale Machine Learning, Istanbul (organising a conference, workshop, ...).
- Birbil, S. . (chair) (24-3-2022). EURO WISDOM Forum YoungWomen4OR Talks: Data Science and Optimization Webinar (participating in a conference, workshop, ...).
- Fajemisin, A. (participant), Maragno, D. (participant), den Hertog, D. (participant) & Birbil, S. . (participant) (22-2-2022 - 1-3-2022). 36th AAAI conference on Artificial Intelligence, Vancouver. Delivering two papers at the AI for Decision Optimization (AI4DO) workshop (participating in a conference, workshop, ...).
- Birbil, S. . (organiser), Postek, K. (organiser) & den Hertog, D. (organiser) (29-9-2021). Machine Learning for Optimization (organising a conference, workshop, ...). https://optimal.uva.nl/content/events/events/2021/09/machine-learning-for-optimization-workshop.html
- Birbil, S. . (organiser) (20-9-2021). Mathematics for Machine Learning, Izmir (organising a conference, workshop, ...). https://nesinkoyleri.org/events/2021-yapay-ogrenme-icin-matematik/
2024
- Kurtz, J., Birbil, S. I., & den Hertog, D. (2024). Counterfactual explanations for linear optimization. ArXiv. https://doi.org/https://arxiv.org/abs/2405.15431, https://doi.org/10.48550/arXiv.2405.15431
- Wasserkrug, S., Boussioux, L., den Hertog, D., Mirzazadeh, F., Birbil, S. I., Kurtz, J., & Maragno, D. (2024). From Large Language Models and Optimization to Decision Optimization CoPilot: A Research Manifesto. ArXiv. https://arxiv.org/abs/2402.16269
2024
- Vogels, L., Mohammadi, R., Schoonhoven, M. & Birbil, Ş. . (2024). Bayesian Structure Learning in Undirected Gaussian Graphical Models: Literature Review with Empirical Comparison. Taylor & Francis. https://doi.org/10.6084/m9.figshare.26880600.v1
This list of publications is extracted from the UvA-Current Research Information System. Questions? Ask the library or the Pure staff of your faculty / institute. Log in to Pure to edit your publications. Log in to Personal Page Publication Selection tool to manage the visibility of your publications on this list. -
Nevenwerkzaamheden
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D4C - Data Science Consultants
Academic adviser for technical details of ongoing projects. -
D4C - Data Science Consultants
Adviser -
Centrum Wiskunde & Informatica
Research associate for at most one day a week.
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D4C - Data Science Consultants
Birbil, İ., Martin, Ö., Onay, G., & Öztoprak, F. (2024). Bolstering stochastic gradient descent with model building. TOP, 32(3), 517-536.