Conference contribution

Leveraging Data Augmentation and Siamese Learning for Predictive Process Monitoring

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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 …

Explainable Optimization: Leveraging Large Language Models for User-Friendly Explanations

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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 …

Revisiting Expected Possession Value in Football: Introducing a U-Net Architecture, Reward and Risk for Passes, and a Benchmark

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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 …

Timed Anti-Alignments for Acyclic Marked Graphs

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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 …

Why Do Users Struggle to Get Insights from Process Mining?

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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 …

MANTA: Materializing Views on Event Data for Context Exploration in Process Analysis

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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 …

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 …

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 …

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 …

A Novel Way to Evaluate Medical Discharge Predictions: A Research Paper

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van der Haas, Y., Medeiros de Carvalho, R., van Dijk, T., van Dongen, B. F., & Plas, R. (2025). A Novel Way to Evaluate Medical Discharge Predictions: A Research Paper. Paper presented at2st International Workshop on Process Mining Applications for Healthcare, PM4H25, Pavia, Italië.

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 …

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 …

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 …

Topology-Agnostic Detection of Temporal Money Laundering Flows in Billion-Scale Transactions

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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 …

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 …

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 …

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 …

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 …

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 …

An insight to nurse workload: predicting activities in the next shift and analyzing bedside alarms influence

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de Carvalho, R. M., Nguyen, H., Heetveld, M., & Luime, J. (2022). An insight to nurse workload: predicting activities in the next shift and analyzing bedside alarms influence. In T. X. Bui (Ed.), Proceedings of the 55th Annual Hawaii International Conference on System Sciences, HICSS 2022 (pp. 4108-4117). IEEE Computer Society. Abstract The effects of Read More …

Predicting Patient Care Acuity: An LSTM Approach for Days-to-day Prediction

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Bekelaar, J. W. R., Luime, J. J., & de Carvalho, R. M. (2023). Predicting Patient Care Acuity: An LSTM Approach for Days-to-day Prediction. In M. Montali, A. Senderovich, & M. Weidlich (Eds.), Process Mining Workshops – ICPM 2022 International Workshops, Revised Selected Papers (pp. 378-390). (Lecture Notes in Business Information Processing; Vol. 468 LNBIP). Springer. https://doi.org/10.1007/978-3-031-27815-0_28 Read More …

Action-Evolution Petri Nets: a Framework for Modeling and Solving Dynamic Task Assignment Problems

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Lo Bianco, R., Dijkman, R. M., Nuijten, W. P. M., & van Jaarsveld, W. L. (2023). Action-Evolution Petri Nets: a Framework for Modeling and Solving Dynamic Task Assignment Problems. In C. Di Francescomarino, A. Burattin, C. Janiesch, & S. Sadiq (Eds.), Business Process Management: 21st International Conference, BPM 2023, Utrecht, The Netherlands, September 11–15, 2023, Read More …

Combining Deep Reinforcement Learning with Search Heuristics for Solving Multi-Agent Path Finding in Segment-based Layouts

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Reijnen, R., Zhang, Y., Nuijten, W. P. M., Senaras, C., & Goldak, M. (2021). Combining Deep Reinforcement Learning with Search Heuristics for Solving Multi-Agent Path Finding in Segment-based Layouts. In 2020 IEEE Symposium Series on Computational Intelligence (SSCI 2020) (pp. 2647-2654). Article 9308584 IEEE Press. https://doi.org/10.1109/SSCI47803.2020.9308584 Abstract A multi-agent path finding (MAPF) problem is concerned Read More …