Tag: Marwan Hassani

  • Marwan Hassani - Dr. Marwan Hassani is assistant professor at the PA group with a focus on Real-Time Process Mining. His research interests include stream data mining, sequential pattern mining of multiple streams, efficient anytime clustering of big data streams and exploration of evolving graph data. He uses customer journey optimizationa and privacy-aware process mining as use cases for his 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 …

Best Paper Award at SAC 2025 for You Xu and Marwan Hassani

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You Xu and Marwan Hassani have received the Best Paper Award Distributed Systems in the ACM/SIGAPP Symposium On Applied Computing (SAC 2025) in Catania, Italy with the paper titled “Leveraging Contrastive Learning and Spatial Encoding for Prediction in Traffic Networks with Expanding Infrastructure“. Congratulations to You and Marwan!

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 …

Seminar Process Analytics (2IMI00) 2024-2025

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Objectives This seminar combines teaching research methods (in preparation for a Master project) with providing students with recent and ongoing research in the area of event data analysis and process analysis. We study recent research articles, book chapters, and Master theses on topics along the entire analysis life-cycle. Through presentation and group discussions, we work Read More …

Advanced Process Mining (2AMI20) 2024-2025

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Objectives After taking this course students should be able to: have a detailed understanding of the entire process mining spectrum and the methodology for process mining analysis can derive and pre-process event logs from raw data and have understand and can work with a specialized form of event data such as event knowledge graphs, or 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 …

Data-driven Support of Coaches in Professional Cycling using Race Performance Prediction

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Karetnikov, A., Nuijten, W., & Hassani, M. (2021). Data-driven Support of Coaches in Professional Cycling using Race Performance Prediction. In P. Pezarat-Correia, J. Vilas-Boas, & J. Cabri (Eds.), icSPORTS 2021 – Proceedings of the 9th International Conference on Sport Sciences Research and Technology Support (pp. 43-53). SciTePress Digital Library. https://doi.org/10.5220/0010656300003059 Abstract In individual sports, the Read More …

Community Detection in Temporal Graphs for Capturing Pass-through Money Laundering Behaviors

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Company Description TMNL (Transaction Monitoring Netherlands) was established by the five largest Dutch banks; and is the 1st initiative in the world fighting financial crime in a multi-bank setting. TMNL combines transaction data from the various banks and makes meaningful connections between this data. TMNL is creating smart models to detect these potentially unusual transactions Read More …

Can we Learn from Outliers? Unsupervised Optimization of Intelligent Vehicle Traffic Management Systems

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Mertens, T., & Hassani, M. (2023). Can we Learn from Outliers? Unsupervised Optimization of Intelligent Vehicle Traffic Management Systems. In M.-R. Amini, S. Canu, A. Fischer, T. Guns, P. Kralj Novak, & G. Tsoumakas (Eds.), Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2022, Grenoble, France, September 19–23, 2022, Proceedings, Part VI Read More …

Conformance checking of process event streams with constraints on data retention

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Zaman, R., Hassani, M., & van Dongen, B. F. (2023). Conformance checking of process event streams with constraints on data retention. Information Systems, 117, Article 102228. https://doi.org/10.1016/j.is.2023.102228 Abstract Conformance checking (CC) techniques in process mining determine the conformity of cases, by means of their event sequences, with respect to a business process model. Online conformance Read More …

Predicting Activities of Interest in the Remainder of Customer Journeys Under Online Settings

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Wolters, L., & Hassani, M. (2023). Predicting Activities of Interest in the Remainder of Customer Journeys Under Online Settings. In M. Montali, A. Senderovich, & M. Weidlich (Eds.), Process Mining Workshops – ICPM 2022 International Workshops, Revised Selected Papers (pp. 145-157). (Lecture Notes in Business Information Processing; Vol. 468 LNBIP). https://doi.org/10.1007/978-3-031-27815-0_11 Abstract Customer journey analysis Read More …

PrefixCDD: Effective Online Concept Drift Detection over Event Streams using Prefix Trees.

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Huete, J., Qahtan, A. A., & Hassani, M. (2023). PrefixCDD: Effective Online Concept Drift Detection over Event Streams using Prefix Trees. In H. Shahriar, Y. Teranishi, A. Cuzzocrea, M. Sharmin, D. Towey, AKM. J. A. Majumder, H. Kashiwazaki, J.-J. Yang, M. Takemoto, N. Sakib, R. Banno, & S. I. Ahamed (Eds.), COMPSAC (pp. 328-333) https://doi.org/10.1109/COMPSAC57700.2023.00051 Read More …

Fine-tuning Pretrained LLMs for Online Anomaly Detection in Customer Journeys of De Volksbank

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Background Customer journey thinking is getting more and more established in companies. Customers are getting more volatile with higher expectations and competition is fierce. With customer journey analytics it is possible to use a personal approach on a large dataset of customer behaviour and customer experience. In the field of customer journey analytics multiple well-known Read More …

Real-Time Process Mining (JM0210-M-6) 2023

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The course starts with an overview of the BPM domain using a set of twenty BPM use cases. These cover four key BPM activities: model (creating a process model to be used for analysis or enactment), enact (using a process model to control and support concrete cases), analyze (analyzing a process using a process model Read More …

Seminar Process Analytics (2IMI00) 2023

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This seminar prepares students for their Master project. By studying recent literature, we discuss and identify how to develop a research question, select the right research method, and plan and conduct the right evaluation. In addition, students get in touch with recent and ongoing research and practical application in the area of Processes and Information Read More …

Advanced Process Mining (2AMI20) 2023

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Many real-life phenomena studied with Data Science methods unfold over time. They often involve many people, objects, agents, machines, entities, etc. that interact with each other while distributed in time and space. Such dynamics are called processes and are present everywhere: in software systems medical treatments, logistics systems, manufacturing, and even entire organizations. Process mining Read More …

Evaluation of Probability Distribution Distance Metrics in Traffic Flow Outlier Detection

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Andersen, E., Chiarandini, M., Hassani, M., Janicke, S., Tampakis, P., & Zimek, A. (2022). Evaluation of Probability Distribution Distance Metrics in Traffic Flow Outlier Detection. In Proceedings – 2022 23rd IEEE International Conference on Mobile Data Management, MDM 2022 (pp. 64-69). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/MDM55031.2022.00030 Abstract Recent approaches have proven the effectiveness Read More …

Online Prediction of Aggregated Retailer Consumer Behaviour

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Spenrath, Y., Hassani, M., & van Dongen, B. F. (2022). Online Prediction of Aggregated Retailer Consumer Behaviour. In J. Munoz-Gama, & X. Lu (Eds.), Process Mining Workshops – ICPM 2021 International Workshops, Revised Selected Papers (pp. 211-223). (Lecture Notes in Business Information Processing; Vol. 433 LNBIP). Springer. https://doi.org/10.1007/978-3-030-98581-3_16 Abstract Predicting the behaviour of consumers provides valuable Read More …

BitBooster: Effective Approximation of Distance Metrics via Binary Operations

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Spenrath, Y., Hassani, M., & Van Dongen, B. F. (2022). BitBooster: Effective Approximation of Distance Metrics via Binary Operations. In H. Va Leong, S. S. Sarvestani, Y. Teranishi, A. Cuzzocrea, H. Kashiwazaki, D. Towey, J-J. Yang, & H. Shahriar (Eds.), Proceedings – 2022 IEEE 46th Annual Computers, Software, and Applications Conference, COMPSAC 2022 (pp. 201-210). Read More …

Real-Time Process Mining (JM0210-M-6) 2022

Posted onAuthorEric VerbeekLeave a comment

The course starts with an overview of the BPM domain using a set of twenty BPM use cases. These cover four key BPM activities: model (creating a process model to be used for analysis or enactment), enact (using a process model to control and support concrete cases), analyze (analyzing a process using a process model Read More …

Efficient Memory Utilization in Conformance Checking of Process Event Streams

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Zaman, R., Hassani, M., & van Dongen, B. F. (2022). Efficient Memory Utilization in Conformance Checking of Process Event Streams. 437-440. https://doi.org/10.1145/3477314.3507217 Abstract Conformance checking (CC) techniques of the process mining field gauge the conformance of the events constituting a case with respect to a business process model. Online conformance checking (OCC) techniques assess such Read More …

Smart Host

Guest Journey Prediction for an Effective Targeted Campaign Planning

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Company Description Smart Host (https://www.smart-host.com) was founded in 2017 and is now one of the leading CRM systems for hotels in Europe. Based in Berlin, Germany we provide a SaaS solution to help hotels maximise their revenue and at the same time become better hosts by gathering valuable information about their guests and their individual Read More …

Seminar Process Analytics (2IMI00) 2022

Posted onAuthorEric VerbeekLeave a comment

This seminar prepares students for their Master project. By studying recent literature, we discuss and identify how to develop a research question, select the right research method, and plan and conduct the right evaluation. In addition, students get in touch with recent and ongoing research and practical application in the area of Processes and Information Read More …

Advanced Process Mining (2AMI20) 2022

Posted onAuthorEric VerbeekLeave a comment

Many real-life phenomena studied with Data Science methods unfold over time. They often involve many people, objectes, agents, machines, entites, etc. that interact with each other while distributed in time and space. Such dynamics are called processes and are present everywhere: in software systems medical treatments, logistics systems, manufacturing, and even entire organizations. Process mining Read More …

A Framework for Efficient Memory Utilization in Online Conformance Checking

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Zaman, R., Hassani, M., & van Dongen, B. F. (2021). A Framework for Efficient Memory Utilization in Online Conformance Checking. arXiv.org. https://arxiv.org/pdf/2112.13640.pdf Abstract Conformance checking (CC) techniques of the process mining field gauge the conformance of the sequence of events in a case with respect to a business process model, which simply put is an Read More …

Prefix Imputation of Orphan Events in Event Stream Processing

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Zaman, R., Hassani, M., & van Dongen, B. F. (2021). Prefix Imputation of Orphan Events in Event Stream Processing. Frontiers in Big Data, 4, [705243]. https://doi.org/10.3389/fdata.2021.705243 Abstract In the context of process mining, event logs consist of process instances called cases. Conformance checking is a process mining task that inspects whether a log file is Read More …

What Averages Do Not Tell – Predicting Real Life Processes with Sequential Deep Learning

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Ketykó, I., Mannhardt, F., Hassani, M., & van Dongen, B. F. (2021). What Averages Do Not Tell – Predicting Real Life Processes with Sequential Deep Learning. CoRR, abs/2110.10225. https://arxiv.org/abs/2110.10225 Abstract Deep Learning is proven to be an effective tool for modeling sequential data as shown by the success in Natural Language, Computer Vision and Signal Read More …

Online Prediction and Recommendation of Volksbank Customer Journey under Concept Drifts

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  Background Within companies customer journey thinking is getting more and more established. Customers are getting more volatile and competition is fierce. With customer journey analytics is it possible to use a personal approach on large dataset of customer behaviour and customer experience. In the field of customer journey analytics multiple well-known fields are combined, Read More …

Predicting Next Touch Point In A Customer Journey – A Use Case In Telecommunication

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Hassani, M., & Habets, S. (2021). Predicting Next Touch Point In A Customer Journey – A Use Case In Telecommunication. In 35th ECMS INTERNATIONAL CONFERENCE ON MODELLING AND SIMULATION (1 ed., Vol. 35, pp. 48-54). (Proceedings – European Council for Modelling and Simulation, ECMS). https://doi.org/10.7148/2021-0048 Abstract Customer journey analysis is rapidly increasing in popularity, as Read More …

Data Minimisation as Privacy and Trust Instrument in Business Processes

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Zaman, R., Hassani, M., & van Dongen, B. F. (Accepted/In press). Data Minimisation as Privacy and Trust Instrument in Business Processes. In Business Process Management Workshops (BPM 2020) Springer. Abstract Data is vital for almost all sorts of business processes and workflows. However, the possession of personal data of other beings bear consequences. Data is Read More …

Facilitating GDPR compliance: the H2020 BPR4GDPR approach

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Lioudakis, G. V., Koukovini, M. N., Papagiannakopoulou, E. I., Dellas, N., Kalaboukas, K., de Carvalho, R. M., Hassani, M., Bracciale, L., Bianchi, G., Juan-Verdejo, A., Alexakis, S., Gaudino, F., Cascone, D., & Barracano, P. (2020). Facilitating GDPR compliance: the H2020 BPR4GDPR approach. In I. O. Pappas, I. O. Pappas, P. Mikalef, L. Jaccheri, J. Krogstie, Read More …