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R.H. Bemthuis MSc (Rob)

Researcher

About Me

Rob Bemthuis is a PhD candidate in the Pervasive Systems Research Group at the University of Twente. He holds a master's degree and a bachelor's degree in Industrial Engineering and Management from the same university, with a specialization in production and logistics management. Rob's research is part of the Big Data for Resilient Logistics (DATAREL) project, which aims to enhance logistic knowledge through innovative Internet of Things (IoT) and Big Data solutions for detecting emerging behaviors. Rob was a visiting scholar in the University of Southern Denmark and Karlsruhe Institute of Technology. Currently, he is coordinating and researching within a sustainable construction logistics project. 

In general, Rob's research interests involve multi-agent systems (MAS), simulation of logistic processes, and machine learning.

Besides his research activities, Rob is an active volunteer in the international community of the University of Twente and Enschede. He served as Treasurer of the PhD Network of the University of Twente (P-NUT) in 2019-2020, held a general board member position in 2020-2021, and was elected Treasurer and Vice-President in 2021-2022. He also chaired the organizing committees of the PhD Day 2019, PhD & PDEng Day 2020, and PhD & PDEng Day 2021 at the University of Twente. Additionally, he participates in various national and regional associations and projects. 

      Expertise

      Engineering & Materials Science
      Clouds
      Edge Computing
      Fog Computing
      Industry
      Internet Of Things
      Logistics
      Mathematics
      Enterprise Architecture
      Physics & Astronomy
      Resources Management

      Publications

      Recent
      Bemthuis, R. H. (2024). Emergent Behaviors in a Resilient Logistics Supply Chain. [PhD Thesis - Research UT, graduation UT, University of Twente]. University of Twente. https://doi.org/10.3990/1.9789036560733
      Bemthuis, R. H., Govers, R., & Lazarova-Molnar, S. (2024). Using Process Mining for Face Validity Assessment in Agent-Based Simulation Models: An Exploratory Case Study. In M. Sellami, W. Gaaloul, M.-E. Vidal, B. van Dongen, & H. Panetto (Eds.), Cooperative Information Systems: 29th International Conference, CoopIS 2023, Groningen, The Netherlands, October 30–November 3, 2023, Proceedings (pp. 311-326). (Lecture Notes in Computer Science; Vol. 14353). Springer Nature. https://doi.org/10.1007/978-3-031-46846-9_17
      Bemthuis, R. H., & Lazarova-Molnar, S. (2023). An Approach for Face Validity Assessment of Agent-Based Simulation Models Through Outlier Detection with Process Mining. In H. A. Proper, L. Pufahl, D. Karastoyanova, M. van Sinderen, & J. Moreira (Eds.), Enterprise Design, Operations, and Computing: 27th International Conference, EDOC 2023, Groningen, The Netherlands, October 30 – November 3, 2023, Proceedings (pp. 134-151). (Lecture Notes in Computer Science; Vol. 14367). Springer Nature. https://doi.org/10.1007/978-3-031-46587-1_8
      Maneschijn, D. G. J. C. , Bemthuis, R. H., Arachchige, J. J. , Bukhsh, F. A. , & Iacob, M. E. (2023). Balancing Simplicity and Complexity in Modeling Mined Business Processes: A User Perspective. In J. Filipe, M. Śmiałek, A. Brodsky, & S. Hammoudi (Eds.), Enterprise Information Systems. ICEIS 2022 (pp. 3-21). (Lecture Notes in Business Information Processing; Vol. 487). Springer Nature. https://doi.org/10.1007/978-3-031-39386-0_1
      Piest, J. P. S. , Bemthuis, R. H., Cutinha, J. A., Arachchige, J. J. , & Bukhsh, F. A. (2023). A Method for Bottleneck Detection, Prediction, and Recommendation Using Process Mining Techniques. In P. Samarati, S. D. C. D. Vimercati, M. van Sinderen, & F. Wijnhoven (Eds.), E-Business and Telecommunications: 18th International Conference on E-Business and Telecommunications, ICETE 2021, Virtual Event, July 6–9, 2021, Revised Selected Papers (pp. 118-136). (Communications in Computer and Information Science (CCIS); Vol. 1795). Springer Nature. https://doi.org/10.1007/978-3-031-36840-0_7
      Bemthuis, R. H., & Lazarova-Molnar, S. (2022). Discovering Agent Models using Process Mining: Initial Approach and a Case Study. In 2022 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom) (pp. 163-172). IEEE. https://doi.org/10.1109/ISPA-BDCloud-SocialCom-SustainCom57177.2022.00028

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      Contact Details

      Visiting Address

      University of Twente
      Faculty of Electrical Engineering, Mathematics and Computer Science
      Zilverling (building no. 11), room 5010
      Hallenweg 19
      7522NH  Enschede
      The Netherlands

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      Mailing Address

      University of Twente
      Faculty of Electrical Engineering, Mathematics and Computer Science
      Zilverling  5010
      P.O. Box 217
      7500 AE Enschede
      The Netherlands

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