Scientific peer reviewed

Task-Free Continual Learning with Dynamic Loss for Online Next Activity Prediction

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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 …

Sustainable Traffic Flow Prediction using Contrastive Learning and Spatial Encoding

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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 …

Neural Combinatorial Optimization for Stochastic Flexible Job Shop Scheduling Problems

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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 …

A Universal Approach to Feature Representation in Dynamic Task Assignment Problems

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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 …

Graph Neural Networks for Job Shop Scheduling Problems: A Survey

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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 …

Can Users Trust Process Mining?

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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 …

Extending Genetic Process Discovery to Reveal Unfairness in Processes

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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 …

Process science: the interdisciplinary study of socio-technical change

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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 …

Constructive Alignment in Process Mining

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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 …

How well can a large language model explain business processes as perceived by users?

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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 …

Unsupervised Anomaly Detection of Prefixes in Event Streams Using Online Autoencoders

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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 …

Autoencoder-Based Detection of Delays, Handovers and Workloads over High-Level Events

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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 …

Handling Catastrophic Forgetting: Online Continual Learning for Next Activity Prediction

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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 …

Outlier-Weighted Traffic Flow Prediction Using Online Autoencoders

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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 …

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

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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

On Inferring a Meaningful Similarity Metric for Customer Behaviour

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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 …

Leveraging Contrastive Learning and Spatial Encoding for Prediction in Traffic Networks with Expanding Infrastructure

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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 …

The IEEE XES Standard for Process Mining: Experiences, Adoption, and Revision [Society Briefs]

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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 …

Uncovering Patterns for Local Explanations in Outcome-based Predictive Process Monitoring

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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 …

Decomposing Process Performance based on Actor Behavior

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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 …

Discovery of Object-Centric Declarative Models

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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 …

Explainable Object-Centric Anomaly Detection: the Role of Domain Knowledge

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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 …

Autoencoder-based Continual Outlier Correlation Detection for Real-Time Traffic Flow Prediction

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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 …

Online Next Activity Prediction Under Concept Drifts

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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 …

Clinical Event Knowledge Graphs: Enriching Healthcare Event Data with Entities and Clinical Concepts – Research Paper

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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 …

Comparing Conformance Checking for Decision Mining: An Axiomatic Approach

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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 …

Customer journeys and process mining – challenges and opportunities

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Halvorsrud, R., Mannhardt, F., Prillard, O., & Boletsis, C. (2024). Customer journeys and process mining – challenges and opportunities. In International Conference on Exploring Service Science (IESS 2.4) (Vol. 62, pp. 05002). (ITM Web of Conferences). https://doi.org/10.1051/itmconf/20246205002

Experience-Based Resource Allocation for Remaining Time Optimization

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Padella, A., Mannhardt, F., Vinci, F., De Leoni, M., & Vanderfeesten, I. (2024). Experience-Based Resource Allocation for Remaining Time Optimization. In A. Marrella, M. Resinas, M. Jans, & M. Rosemann (Eds.), Business Process Management: 22nd International Conference, BPM 2024, Krakow, Poland, September 1–6, 2024, Proceedings (pp. 345-362). Article Chapter 20 (Lecture Notes in Computer Science (LNCS); Read More …

The Quest for the Comprehensive Customer Journey – A Case Study from a C2C Marketplace

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Mannhardt, F., Halvorsrud, R., Meironas, O., & Brurok, L. (2024). The Quest for the Comprehensive Customer Journey – A Case Study from a C2C Marketplace. In Business Process Management: Blockchain, Robotic Process Automation, Central and Eastern European, Educators and Industry Forum (Vol. 527, pp. 451-461). Article Chapter 33 (Lecture Notes in Business Information Processing; Vol. 527). https://doi.org/10.1007/978-3-031-70445-1_33

Generating Event Logs with CPN IDE

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Verbeek, E., & Fahland, D. (2023). Generating Event Logs with CPN IDE. In Doctoral Consortium and Demo Track 2023 at the International Conference on Process Mining, ICPM-DCDT 2023 (CEUR Workshop Proceedings; Vol. 3648). Abstract This extended abstract introduces the event log generation facility of CPN IDE. CPN IDE has replaced CPN Tools as a tool Read More …

The biggest business process management problems to solve before we die

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Beerepoot, I., Di Ciccio, C., Reijers, H. A., Rinderle-Ma, S., Bandara, W., Burattin, A., Calvanese, D., Chen, T., Cohen, I., Depaire, B., Di Federico, G., Dumas, M., van Dun, C., Fehrer, T., Fischer, D. A., Gal, A., Indulska, M., Isahagian, V., Klinkmüller, C., … Zerbato, F. (2023). The biggest business process management problems to solve Read More …

The Influence of Business Process Management System Implementation on an Organization’s Process Orientation: A Case Study of a Financial Service Provider

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Ozkan, B., Koops, M., Türetken, O., & Reijers, H. A. (2023). The Influence of Business Process Management System Implementation on an Organization’s Process Orientation: A Case Study of a Financial Service Provider. Information Systems Management, 1-22. Advance online publication. https://doi.org/10.1080/10580530.2023.2286980 Abstract This study investigates the influence of Business Process Management System (BPMS) implementation on an Read More …

Online Prediction Threshold Optimization Under Semi-deferred Labelling

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Spenrath, Y., Hassani, M., & van Dongen, B. F. (2024). Online Prediction Threshold Optimization Under Semi-deferred Labelling. In T. Palpanas, & H. V. Jagadish (Eds.), 8th International workshop on Data Analytics solutions for Real-LIfe APplications (DARLI-AP) (CEUR Workshop Proceedings; Vol. 3651). CEUR-WS.org. https://ceur-ws.org/Vol-3651/ Abstract In supermarket loyalty campaigns, shoppers collect stamps to redeem limited-time luxury Read More …

Multi-Perspective Concept Drift Detection: Including the Actor Perspective

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Klijn, E. L., Mannhardt, F., & Fahland, D. (2024). Multi-perspective Concept Drift Detection: Including the Actor Perspective. In G. Guizzardi, F. Santoro, H. Mouratidis, & P. Soffer (Eds.), Advanced Information Systems Engineering – 36th International Conference, CAiSE 2024, Proceedings (pp. 141-157). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Read More …

Event Knowledge Graphs for Auditing: A Case Study

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Klijn, E. L., Preuss, D., Imeri, L., Baumann, F., Mannhardt, F., & Fahland, D. (2024). Event Knowledge Graphs for Auditing: A Case Study. In J. De Smedt, & P. Soffer (editors), Process Mining Workshops: ICPM 2023 International Workshops, Rome, Italy, October 23–27, 2023, Revised Selected Papers (blz. 84-97). (Lecture Notes in Business Information Processing (LNBIP); Read More …

Implementing Object-Centric Event Data Models in Event Knowledge Graphs

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Swevels, A., Fahland, D., & Montali, M. (2024). Implementing Object-Centric Event Data Models in Event Knowledge Graphs. In J. De Smedt, & P. Soffer (Eds.), Process Mining Workshops – ICPM 2023 International Workshops, 2023, Revised Selected Papers (pp. 431-443). (Lecture Notes in Business Information Processing; Vol. 503 LNBIP). https://doi.org/10.1007/978-3-031-56107-8_33 Abstract Recent advances in object-centric process Read More …

Using Machine Learning Techniques to Support the Emergency Department

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van Delft, R. A. J. J., & de Carvalho, R. M. (2022). Using Machine Learning Techniques to Support the Emergency Department. Computing and Informatics, 41(1), 154-171. https://doi.org/10.31577/CAI_2022_1_154 Abstract This research lays down foundations for a stronger presence of machine learning in the emergency department. Using machine learning to make predictions on a patient’s situation can Read More …

From predictions to recommendations: Tackling bottlenecks and overstaying in the Emergency Room through a sequence of Random Forests

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Verdaasdonk, M. J. A., & de Carvalho, R. M. (2022). From predictions to recommendations: Tackling bottlenecks and overstaying in the Emergency Room through a sequence of Random Forests. Healthcare Analytics, 2, Article 100040. https://doi.org/10.1016/j.health.2022.100040 Abstract One of the goals to improve the quality of care in hospitals is to set a maximum of four hours Read More …

Domain engineering for customer experience management

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Benzarti, I., Mili, H., Medeiros de Carvalho, R., & Leshob, A. (2022). Domain engineering for customer experience management. Innovations in Systems and Software Engineering, 18(1), 171-191. https://doi.org/10.1007/s11334-021-00426-2 Abstract Customer experience management (CXM) denotes a set of practices, processes, and tools, that aim at personalizing a customer’s interactions with a company around the customer’s needs and Read More …