Sidorova, N., & Medeiros de Carvalho, R. (2026). Uncharted Workflows: Process Mining Perspectives in Health. In J. Mendling, S. Leemans, B. F. van Dongen, & H. Reijers (Eds.), Mining a Scientist’s Process: Essays Dedicated to Wil van der Aalst on the Occasion of His 60th Birthday (pp. 648-661). (Lecture Notes in Computer Science (LNCS); Vol. 16480). Read More …
van Straten, S., Padella, A., & Hassani, M. (2026). Leveraging Data Augmentation and Siamese Learning for Predictive Process Monitoring. In C. Cappiello, O. Hartig, M. Sellami, & A. Ouni (Eds.), Cooperative Information Systems: 31st International Conference, CoopIS 2025, Marbella, Spain, October 20–22, 2025, Proceedings (pp. 70-87). (Lecture Notes in Computer Science (LNCS); Vol. 15535). Springer. https://doi.org/10.1007/978-3-032-15538-2_5 Abstract Read More …
Mendling, J., Leemans, S. J. J., Dongen, van, B. F., & Reijers, H. A. (Eds.) (2026). Mining a Scientist’s Process: Essays Dedicated to Wil van der Aalst on the Occasion of His 60th Birthday. (Lecture Notes in Computer Science; Vol. 16480). Springer. https://doi.org/10.1007/978-3-032-17618-9
Seidel, A., Weske, M., Montali, M., Rivkin, A., Reichert, M., van der Werf, J. M. E. M., van der Aalst, W. M. P., Breitmayer, M., Liss, L., van Detten, J. N., Jalali, A., Khayatbashi, S., König, M., Lichtenstein, T., Rinderle-Ma, S., Weber, B., Soffer, P., Rossi, L., Calegari Garcia, D., Delgado, A., Dijkman, R., Winkler, Read More …
Fahland, D., & Montali, M. (2026). What is an Object-Centric Case? An Exploration. In J. Mendling, S. Leemans, B. F. van Dongen, & H. Reijers (Eds.), Mining a Scientist’s Process: Essays Dedicated to Wil van der Aalst on the Occasion of His 60th Birthday (pp. 398-425). (Lecture Notes in Computer Science; Vol. 16480 LNCS). Springer. https://doi.org/10.1007/978-3-032-17618-9_28 Read More …
Mozafari Mehr, A. S., M. de Carvalho, R., & van Dongen, B. (2023). Explainable conformance checking: Understanding patterns of anomalous behavior. Engineering Applications of Artificial Intelligence, 126(Part B.), Article 106827. https://doi.org/10.1016/j.engappai.2023.106827 Abstract Anomaly detection in the execution of business processes in the organizations has a high level of complexity due to the consideration of various Read More …
Biemans, B. C. M., Troubil, P., Grau, I., & Nuijten, W. P. M. (2025). Explainable Optimization: Leveraging Large Language Models for User-Friendly Explanations. In R. Guidotti, U. Schmid, & L. Longo (Eds.), Explainable Artificial Intelligence: Third World Conference, xAI 2025, Istanbul, Turkey, July 9–11, 2025, Proceedings (Vol. Part III, pp. 44-67). (Communications in Computer and Read More …
Overmeer, T., Janssen, T., & Nuijten, W. P. M. (2025). Revisiting Expected Possession Value in Football: Introducing a U-Net Architecture, Reward and Risk for Passes, and a Benchmark. In R. Arellano, P. Morouco, & C. Capelli (Eds.), Proceedings of the 13th International Conference on Sport Sciences Research and Technology Support, IcSPORTS 2025 (pp. 100-109). (International Read More …
Sommers, D., Sidorova, N., & van Dongen, B. (2026). In system alignments we trust! Explainable alignments via projections. Information Systems, 136, Article 102631. https://doi.org/10.1016/j.is.2025.102631 Abstract Alignments are a well-known process mining technique for reconciling system logs and normative process models. Evidence of certain behaviors in a real system may only be present in one representation Read More …
Bavaro, S., Chatain, T., & van Dongen, B. F. (2025). Timed Anti-Alignments for Acyclic Marked Graphs. In M. Köhler-Bußmeier, D. Moldt, H. Rölke, R. Bergenthum, A. Rivkin, J. M. E. M. van der Werf, J. Desel, & L. Petrucci (Eds.), PN-WS 2025 : Joint Workshop Proceedings of PNSE, ATAED, and PeNGE at PETRI NETS 2025: Read More …
Tentina, I., Zerbato, F., Mannhardt, F., & van Dongen, B. F. (2025). Why Do Users Struggle to Get Insights from Process Mining? In J. De Weerdt, J.-R. Rehse, & H. Reijers (Eds.), 2025 7th International Conference on Process Mining, ICPM 2025 Article 11220617 Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICPM66919.2025.11220617 (best student paper award) Abstract Read More …
Basmer, M., Ueck, H., Fahland, D., & Weidlich, M. (2025). MANTA: Materializing Views on Event Data for Context Exploration in Process Analysis. In A. Senderovich, C. Cabanillas, I. Vanderfeesten, & H. A. Reijers (Eds.), Business Process Management: 23rd International Conference, BPM 2025, Seville, Spain, August 31 – September 5, 2025, Proceedings (pp. 51-68). (Lecture Notes in Computer Science Read More …
van Montfort, J., Bernard, H. F., & Fahland, D. (2025). From Process Mining to Thinking Assistants in Logistics. In J. vom Brocke, J. Mendling, & M. Rosemann (Eds.), Business Process Management Cases Vol. 3: Implementation in Practice (pp. 73-86). Springer Nature. https://doi.org/10.1007/978-3-031-80793-0_6 Abstract (a) Situation faced: Vanderlande Industries BV, or Vanderlande for short (VI), is Read More …
Verbeek, T., Yao, R., & Hassani, M. (2025). Task-Free Continual Learning with Dynamic Loss for Online Next Activity Prediction. In A. Delgado, & T. Slaats (Eds.), Process Mining Workshops: ICPM 2024 International Workshops, Lyngby, Denmark, October 14–18, 2024, Revised Selected Papers (pp. 693-705). (Lecture Notes in Business Information Processing; Vol. 533). Springer. https://doi.org/10.1007/978-3-031-82225-4_51 Abstract Continual learning, known Read More …
Xu, Y., & Hassani, M. (2025). Sustainable Traffic Flow Prediction using Contrastive Learning and Spatial Encoding. ACM SIGAPP Applied Computing Review, 25(2), 31-46. https://doi.org/10.1145/3746626.3746629 Abstract Urban traffic networks evolve continuously as cities add and relocate sensors, yet most prediction pipelines must be retrained from scratch to exploit these new data sources. Such retraining is costly Read More …
Smit, I. G., Wu, Y., Troubil, P., Zhang, Y., & Nuijten, W. P. M. (2025). Neural Combinatorial Optimization for Stochastic Flexible Job Shop Scheduling Problems. In T. Walsh, J. Shah, & Z. Kolter (Eds.), Proceedings of the 39th Annual AAAI Conference on Artificial Intelligence: AAAI-25 Technical Tracks 25 (pp. 26678-26687). (Proceedings of the AAAI Conference Read More …
Lo Bianco, R., Dijkman, R. M., & Nuijten, W. P. M. (2024). A Universal Approach to Feature Representation in Dynamic Task Assignment Problems. In A. Marrella, M. Resinas, M. Jans, & M. Rosemann (Eds.), Business Process Management Forum: BPM 2024 Forum, Krakow, Poland, September 1-6, 2024, Proceedings (pp. 197-213). Springer. https://doi.org/10.1007/978-3-031-70418-5_12 Abstract Dynamic task assignment Read More …
Smit, I. G., Zhou, J., Reijnen, R., Wu, Y., Chen, J., Zhang, C., Bukhsh, Z., Zhang, Y. & Nuijten, W. P. M. (2025). Graph Neural Networks for Job Shop Scheduling Problems: A Survey. Computers and Operations Research, 176, Article 106914. https://doi.org/10.1016/j.cor.2024.106914 Abstract Job shop scheduling problems (JSSPs) represent a critical and challenging class of combinatorial Read More …
Tentina, I., Mannhardt, F., Zerbato, F., & van Dongen, B. (2025). Can Users Trust Process Mining? In K. Wecel (Ed.), Business Information Systems: 25th International Conference, BIS 2025, Poznań, Poland, June 25–27, 2025, Proceedings (pp. 137-151). (Lecture Notes in Business Information Processing (LNBIP); Vol. 554). Springer. https://doi.org/10.1007/978-3-031-94193-1_11 Abstract Process mining enables organizations to gain insights Read More …
Muskan, Mannhardt, F., & van Dongen, B. (2025). Extending Genetic Process Discovery to Reveal Unfairness in Processes. In A. Delgado, & T. Slaats (editors), Process Mining Workshops: ICPM 2024 International Workshops, Lyngby, Denmark, October 14–18, 2024, Revised Selected Papers (blz. 751-763). (Lecture Notes in Business Information Processing (LNBIP); Vol. 533). Springer. https://doi.org/10.1007/978-3-031-82225-4_55 Abstract Fairness is an essential Read More …
vom Brocke, J., van der Aalst, W. M. P., Berente, N., van Dongen, B. F., Grisold, T., Kremser, W., Mendling, J., Pentland, B. T., Roeglinger, M., Rosemann, M., & Weber, B. (2024). Process science: the interdisciplinary study of socio-technical change. Process Science, 1(1), Artikel 1. https://doi.org/10.1007/s44311-024-00001-5 Abstract Process science is the interdisciplinary study of socio-technical Read More …
Brunings, M., Fahland, D., & van Dongen, B. F. (2025). Constructive Alignment in Process Mining. In A. Delgado, & T. Slaats (Eds.), Process Mining Workshops: ICPM 2024 International Workshops, Lyngby, Denmark, October 14–18, 2024, Revised Selected Papers (pp. 105-116). (Lecture Notes in Business Information Processing (LNBIP); Vol. 533). Springer. https://doi.org/10.1007/978-3-031-82225-4_8 Abstract Constructive alignment is a Read More …
Fahland, D., Fournier, F., Limonad, L., Skarbovsky, I., & Swevels, A. J. E. (2025). How well can a large language model explain business processes as perceived by users? Data and Knowledge Engineering, 157, Article 102416. https://doi.org/10.1016/j.datak.2025.102416 Abstract Large Language Models (LLMs) are trained on a vast amount of text to interpret and generate human-like textual Read More …
Musaj, Z., & Hassani, M. (2025). Unsupervised Anomaly Detection of Prefixes in Event Streams Using Online Autoencoders. In M. Comuzzi, D. Grigori, M. Sellami, & Z. Zhou (Eds.), Cooperative Information System: 30th International Conference, CoopIS 2024, Porto, Portugal, November 19–21, 2024, Proceedings (pp. 93-110). Springer. https://doi.org/10.1007/978-3-031-81375-7_6 Abstract In this work we address the problem of Read More …
Verwijst, I., Mennens, R., Scheepens, R., & Hassani, M. (2025). Autoencoder-Based Detection of Delays, Handovers and Workloads over High-Level Events. In M. Comuzzi, D. Grigori, M. Sellami, & Z. Zhou (Eds.), Cooperative Information Systems: 30th International Conference, CoopIS 2024, Porto, Portugal, November 19–21, 2024, Proceedings (pp. 111-128). (Lecture Notes in Computer Science (LNCS); Vol. 15506). Read More …
Verbeek, T., & Hassani, M. (2025). Handling Catastrophic Forgetting: Online Continual Learning for Next Activity Prediction. In M. Comuzzi, D. Grigori, M. Sellami, & Z. Zhou (Eds.), Cooperative Information Systems – 30th International Conference, CoopIS 2024, Proceedings: 30th International Conference, CoopIS 2024, Porto, Portugal, November 19–21, 2024, Proceedings (pp. 225-242). (Lecture Notes in Computer Science Read More …
Choudhary, H., Alkhodre, A. B., & Hassani, M. (2025). Outlier-Weighted Traffic Flow Prediction Using Online Autoencoders. In R. Chbeir, S. Ilarri, Y. Manolopoulos, P. Z. Revesz, J. Bernardino, & C. K. Leung (Eds.), Database Engineered Applications: 28th International Symposium, IDEAS 2024, Bayonne, France, August 26–29, 2024, Proceedings (pp. 203-219). (Lecture Notes in Computer Science (LNCS); Read More …
Tariq, H., & Hassani, M. (2025). Topology-Agnostic Detection of Temporal Money Laundering Flows in Billion-Scale Transactions. In R. Meo, & F. Silvestri (Eds.), Machine Learning and Principles and Practice of Knowledge Discovery in Databases: International Workshops of ECML PKDD 2023, Turin, Italy, September 18–22, 2023, Revised Selected Papers, Part V (pp. 402-419). (Communications in Computer Read More …
Hassani, M., Koschmider, A., Comuzzi, M., Maggi, F. M., & Pufahl, L. (Eds.) (2022). Proceedings of the ICPM Doctoral Consortium and Demo Track 2022 co-located with 4th International Conference on Process Mining (ICPM 2022), Bolzano, Italy, October, 2022. (CEUR Workshop Proceedings; Vol. 3299). CEUR-WS.org. https://ceur-ws.org/Vol-3299
van den Berg, S., & Hassani, M. (2021). On Inferring a Meaningful Similarity Metric for Customer Behaviour. In Y. Dong, N. Kourtellis, B. Hammer, & J. A. Lozano (Eds.), Machine Learning and Knowledge Discovery in Databases: Applied Data Science Track – European Conference, ECML PKDD 2021, Proceedings (pp. 234-250). (Lecture Notes in Computer Science (including Read More …
Xu, Y., & Hassani, M. (2025). Leveraging Contrastive Learning and Spatial Encoding for Prediction in Traffic Networks with Expanding Infrastructure. In SAC ’25: Proceedings of the 40th ACM/SIGAPP Symposium on Applied Computing (pp. 1590-1599). Association for Computing Machinery, Inc.. https://doi.org/10.1145/3672608.3707852 Abstract In modern urban environments, accurate traffic prediction is vital for managing congestion and optimizing Read More …
Wynn, M. T., Van Der Aalst, W., Verbeek, E., & Di Stefano, B. (2024). The IEEE XES Standard for Process Mining: Experiences, Adoption, and Revision [Society Briefs]. IEEE Computational Intelligence Magazine, 19(1), 20-23. https://doi.org/10.1109/MCI.2023.3333141 Abstract The IEEE Standards Association (SA) officially published the XES Standard as IEEE Std 1849-2016: IEEE Standard for eXtensible Event Stream Read More …
Buliga, A., Vazifehdoostirani, M., Genga, L., Lu, X., Dijkman, R. M., Di Francescomarino, C., Ghidini, C., & Reijers, H. A. (2024). Uncovering Patterns for Local Explanations in Outcome-based Predictive Process Monitoring. In A. Marrella, M. Resinas, M. Jans, & M. Rosemann (editors), Business Process Management: 22nd International Conference, BPM 2024, Krakow, Poland, September 1–6, 2024, Read More …
Klijn, E. L., Tentina, I., Fahland, D., & Mannhardt, F. (2024). Decomposing Process Performance based on Actor Behavior. In X. Lu, L. Pufahl, & M. Song (editors), 2024 6th International Conference on Process Mining, ICPM 2024 (blz. 129-136). Artikel 10680657 Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICPM63005.2024.10680657 Abstract Process performance analysis based on event logs Read More …
Christfort, A. K. F., Rivkin, A., Fahland, D., Hildebrandt, T. T., & Slaats, T. (2024). Discovery of Object-Centric Declarative Models. In X. Lu, L. Pufahl, & M. Song (editors), 2024 6th International Conference on Process Mining, ICPM 2024 (blz. 121-128). Artikel 10680680 Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICPM63005.2024.10680674 Abstract Object-centric process mining views processes Read More …
Berti, A., Jessen, U., van der Aalst, W. M. P., & Fahland, D. (2024). Explainable Object-Centric Anomaly Detection: the Role of Domain Knowledge. In BPM-D 2024: Proceedings of the Best Dissertation Award, Doctoral Consortium, and Demonstration & Resources Forum at BPM 2024 co-located with 22nd International Conference on Business Process Management (BPM 2024) Krakow, Poland, Read More …
Choudhary, H., & Hassani, M. (2024). Autoencoder-based Continual Outlier Correlation Detection for Real-Time Traffic Flow Prediction. In 39th Annual ACM Symposium on Applied Computing, SAC 2024 (pp. 218-220) https://doi.org/10.1145/3605098.3636162 Abstract In urban landscapes, traffic congestion, often identified by outlier events like accidents or constructions, poses a significant challenge. These outliers result in abrupt traffic fluctuations, Read More …
Kosciuszek, T., & Hassani, M. (2024). Online Next Activity Prediction Under Concept Drifts. In J. P. A. Almeida, C. Di Ciccio, & C. Kalloniatis (Eds.), Advanced Information Systems Engineering Workshops: CAiSE 2024 International Workshops, Limassol, Cyprus, June 3–7, 2024, Proceedings (pp. 335-346). (Lecture Notes in Business Information Processing; Vol. 521). https://doi.org/10.1007/978-3-031-61003-5_28 Abstract Existing research in Read More …
Aali, M. N., Mannhardt, F., & Toussaint, P. J. (2024). Clinical Event Knowledge Graphs: Enriching Healthcare Event Data with Entities and Clinical Concepts – Research Paper. In J. De Smedt, & P. Soffer (Eds.), Process Mining Workshops – ICPM 2023 International Workshops, 2023, Revised Selected Papers (pp. 296-308). (Lecture Notes in Business Information Processing; Vol. Read More …
Banham, A., ter Hofstede, A. H. M., Leemans, S. J. J., Mannhardt, F., Andrews, R., & Wynn, M. T. (2024). Comparing Conformance Checking for Decision Mining: An Axiomatic Approach. IEEE Access, 12, 60276-60298. Article 10504896. https://doi.org/10.1109/ACCESS.2024.3391234 Abstract Process mining uses historical executions of business processes (as recorded in an event log) to uncover and describe Read More …
