Victoria Degeler Computer scientist specializing in smart systems creation

Publications

2026

• I. El Ghabi, R. N. Alief, D. Dustegor, G. Henckens, A. Lazovik, V. Degeler (2026) “GNN-Based State Estimation for Urban Wastewater Digital Twins”, ACM Symposium on Applied Computing, Accepted/In Press

2025

• M. Lotfian Delouee, V. Degeler, P. Amthor, M. C. Schut, B. Koldehofe (2025) “Pattern-level Privacy Protection in Event-based Systems”, SN Computer Science, Springer, Accepted/In Press.
• Karabulut, E., Daza, D., Groth, P., and Degeler, V. (2025) “Discovering Association Rules in High-Dimensional Small Tabular Data”, The 1st International Workshop on Advanced Neuro-Symbolic Applications (ANSyA) co-located with ECAI 2025. Accepted/In press. arxiv doi: 10.48550/arXiv.2509.20113
• Tello, A.; van het Loo, H.; Lazovik, A.; Degeler, V. (2025). Towards Graph Foundation Models for Water Distribution Networks. The University of Sheffield. the 21st Computing and Control in the Water Industry Conference (CCWI 2025). doi: 10.15131/shef.data.29921231.v1
• van den Barg J.A.A., Degeler V. (2025) Earth Science Digital Twins: A Systematic Literature Review. The 2nd International Conference on Engineering Digital Twins (EDTconf). Accepted/In Press. [pdf]
• Karabulut, E., Groth, P., and Degeler, V. (2025) Pyaerial: Scalable Association Rule Mining from Tabular Data. SoftwareX. Volume 31, 102341. doi: 10.1016/j.softx.2025.102341
• Karabulut, E., Groth, P., & Degeler, V. (2025) Learning Semantic Association Rules from Internet of Things Data. Neurosymbolic Artificial Intelligence. 2025;1 [pdf]. doi: 10.1177/29498732251377518
• E. Peltonen, S. Bayhan, D. Bermbach, S. Buschjager, V. Degeler, A. Y. Ding et al. (2025) Rethinking Computing Systems in the Era of Climate Crisis: A Call for a Sustainable Computing Continuum. IEEE Internet Computing. [pdf] doi: 10.1109/MIC.2025.3566642
• Karabulut, E., Groth, P. T., & Degeler, V. O. (2025) Neurosymbolic Association Rule Mining from Tabular Data. Proceedings of the 19th International Conference on Neurosymbolic Learning and Reasoning (NeSy). PMLR 284:565-588. [pdf]. arXiv doi: 10.48550/arXiv.2504.19354; [PMLR url]
• H. Truong, A. Tello, A. Lazovik, V. Degeler (2025) DiTEC-WDN: A Large-Scale Dataset of Hydraulic Scenarios across Multiple Water Distribution Networks. Scientific Data 12, 1733. doi: 10.1038/s41597-025-06026-0
• Tello, A., Degeler, V., (2025) Contrasting Global and Local Representations for Human Activity Recognition using Graph Neural Networks. In Proceedings of the 40th ACM/SIGAPP Symposium on Applied Computing (SAC ‘25). Association for Computing Machinery, New York, NY, USA, 630–637. [pdf] doi: 10.1145/3672608.3707743

2024

• Karabulut, E., Groth, P. T., & Degeler, V. O. (2024) 3K: Knowledge-Enriched Digital Twin Framework. In Proceedings of the 14th International Conference on the Internet of Things (IoT ‘24). Association for Computing Machinery, New York, NY, USA, 188–193., doi: 10.1145/3703790.3703834. [pdf]
• Huang, Y., Karabulut, E., & Degeler, V. O. (2024) Large Language Model for Ontology Learning In Drinking Water Distribution Network Domain. In EKAW 2024 Workshops, Tutorials, Posters and Demos, 24th International Conference on Knowledge Engineering and Knowledge Management (EKAW 2024), November 26-28, 2024, Amsterdam, The Netherlands. [pdf]
• M. Lotfian Delouee, D.G. Pernes, V. Degeler, B. Koldehofe. (2024) Poster: Towards Federated LLM-Powered CEP Rule Generation and Refinement. In Proceedings of the 18th ACM International Conference on Distributed and Event-Based Systems (DEBS’24). Association for Computing Machinery, New York, NY, USA, 185–186. doi: 10.1145/3629104.3672429. [pdf]
• V. Degeler, M. Hadadian, E. Karabulut, A. Lazovik, H. van het Loo, A. Tello, H. Truong (2024) DiTEC: Digital Twin for Evolutionary Changes in Water Distribution Networks. Leveraging Applications of Formal Methods, Verification and Validation. Application Areas. ISoLA 2024. Lecture Notes in Computer Science, vol 15223. Springer. doi: 10.1007/978-3-031-75390-9_5; [pdf]
• A. Khalil, M. Lotfian Delouee, V. Degeler, T. Meuser, A. F. Anta and B. Koldehofe, “Driving Towards Efficiency: Adaptive Resource-Aware Clustered Federated Learning in Vehicular Networks,” 2024 22nd Mediterranean Communication and Computer Networking Conference (MedComNet), Nice, France, 2024, pp. 1-10, doi: 10.1109/MedComNet62012.2024.10578208; [pdf]
• van Etten, T.; Degeler, V. and Luo, D. (2024). Large-Scale Forecasting of Electric Vehicle Charging Demand Using Global Time Series Modeling. In Proceedings of the 10th International Conference on Vehicle Technology and Intelligent Transport Systems (VEHITS); SciTePress, pages 40-51. doi: 10.5220/0012555400003702; [pdf]
• H. Truong, A. Tello, A. Lazovik, V. Degeler (2024) Graph Neural Networks for Pressure Estimation in Water Distribution Systems, Water Resources Research, 60, e2023WR036741. doi:10.1029/2023WR036741; [pdf]
• A. Tello, H. Truong, A. Lazovik, V. Degeler (2024) Large-Scale Multipurpose Benchmark Datasets For Assessing Data-Driven Deep Learning Approaches For Water Distribution Networks. Engineering Proceedings. 2024; 69(1):50. doi: 10.3390/engproc2024069050; [pdf]; Dataset: 10.5281/zenodo.10974086
• M. H. Nejad Yousefi, V. Degeler and A. Lazovik, “Self-Adaptive Service Selection for Machine Learning Continuous Delivery,” 2024 IEEE International Conference on Web Services (ICWS), Shenzhen, China, 2024, pp. 1048-1056, doi: 10.1109/ICWS62655.2024.00123. [pdf]
• ML Delouee, V Degeler, P Amthor, B Koldehofe (2024). APP-CEP: Adaptive Pattern-level Privacy Protection in Complex Event Processing Systems. In Proceedings of the 10th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP. pp. 486-497. ISBN 978-989-758-683-5. doi: 10.5220/0012358700003648; [pdf].
• Karabulut, E., Pileggi, S. F., Groth, P., & Degeler, V. (2024). Ontologies in Digital Twins: A Systematic Literature Review. Future Generation Computer Systems, vol. 153, pp. 442-456, April 2024. doi:10.1016/j.future.2023.12.013. [pdf]
• Tello, A., Degeler, V., Lazovik, A. (2024) Too Good To Be True: accuracy overestimation in (re)current practices for Human Activity Recognition. IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops), Biarritz, France, 2024, pp. 511-517, doi: 10.1109/PerComWorkshops59983.2024.10503465; [pdf]

2023

• Karabulut, E., Degeler, V., Groth, P. (2023). Semantic Association Rule Learning from Time Series Data and Knowledge Graphs. 2nd International Workshop on Semantic Industrial Information Modelling, 7th November 2023, Athens, Greece, co-located with 22nd International Semantic Web Conference (ISWC 2023). [pdf]; arXiv preprint: arXiv.2310.07348.
• M. Lotfian Delouee, B. Koldehofe, V. Degeler, Towards Pattern-Level Privacy Protection in Distributed Complex Event Processing, In Proceedings of the 17th ACM International Conference on Distributed and Event-based Systems (DEBS ‘23). Association for Computing Machinery, New York, NY, USA, 185–186. doi: 10.1145/3583678.3603278; [pdf]
• Yousefi, M.H.N., Degeler, V., Lazovik, A. (2023). Empowering Machine Learning Development with Service-Oriented Computing Principles. In: Service-Oriented Computing. SummerSOC 2023. Communications in Computer and Information Science, vol 1847. Springer, Cham.doi: 10.1007/978-3-031-45728-9_2; [pdf]
• M. Lotfian Delouee, B. Koldehofe, and V. Degeler. 2023. AQuA-CEP: Adaptive Quality-Aware Complex Event Processing in the Internet of Things. In Proceedings of the 17th ACM International Conference on Distributed and Event-based Systems (DEBS). Association for Computing Machinery, New York, NY, USA, 13–24. doi: 10.1145/3583678.3596884 [pdf]
• Y. Demchenko, V. Degeler, A. Oprescu and S. Brewer, “Professional and 21st Century Skills for Data Driven Digital Economy,” 2023 IEEE Global Engineering Education Conference (EDUCON), 2023, pp. 1-8, doi: 10.1109/EDUCON54358.2023.10125263; [pdf]

Earlier

• R. Riesebos, V. Degeler and A. Tello, “Smartphone-Based Real-Time Indoor Positioning Using BLE Beacons,” 2022 IEEE 18th International Conference on Automation Science and Engineering (CASE), 2022, pp. 1281-1288, doi: 10.1109/CASE49997.2022.9926639; [pdf]
• M. L. Delouee, B. Koldehofe and V. Degeler, “Towards adaptive quality-aware Complex Event Processing in the Internet of Things,” 2022 18th International Conference on Mobility, Sensing and Networking (MSN), Guangzhou, China, 2022, pp. 571-575, doi: 10.1109/MSN57253.2022.00095; [pdf]
• Tello, A., & Degeler, V. (2022). Digital Twins: An enabler for digital transformation. In Digital Transformation: A Guide for Managers (pp. 176–203). Groningen Digital Business Centre (GDBC), University of Groningen. doi: 10.5281/zenodo.7647493; [pdf]
• Al-Saudi K, Degeler V, Medema M. Energy Consumption Patterns and Load Forecasting with Profiled CNN-LSTM Networks. Processes. 2021; 9(11):1870. doi:10.3390/pr9111870; [pdf]
• Degeler, V., Heydenrijk-Ottens, L., Luo, D., van Oort, N., & van Lint, H. (2021). Unsupervised approach towards analysing the public transport bunching swings formation phenomenon. Public Transport, 1-23. doi: 10.1007/s12469-020-00251-z; [pdf]
• Mantouka, E. G., Vlahogianni, E. I., Papacharalampous, A. E., Heydenrijk-Ottens, L., Shelat, S., Degeler, V., & van Lint, H. (2019). Understanding Travel Behavior through Travel Happiness. Transportation Research Record, 2673(4), 889-897. doi: 10.1177/0361198119836761; [pdf]
• V. Degeler, L. Heydenrijk-Ottens, D. Luo, N. van Oort and H. van Lint. Unsupervised approach to bunching swings phenomenon analysis, Conference on Advanced Systems in Public Transport and TransitData (CASPT), 2018. [pdf]
• L. Heydenrijk-Ottens, V. Degeler, D. Luo, N. van Oort and H. van Lint. Supervised learning: Predicting passenger load in public transport, Conference on Advanced Systems in Public Transport and TransitData (CASPT), 2018. [pdf]
• E. Mantouka, A. Papacharalampous, I. Stroumpou, L. Heydenrijk, S. Shelat, P. Chamoso Santos, J. Guisado-Gamez, V. Degeler, E. Mitsakis, E. Vlahogianni, J. Larriba-Pey, Urban Travel Behaviour: A Cross-country Comparison, 7th Symposium of the European Association for Research in Transportation (hEART), 2018. [pdf]
• G. Di Pasquale, V. Degeler, A. Papacharalampous, E. Mantouka, J.L. Larriba, Multimodal travel companion enabled by Artificial Intelligence, 25th ITS World Congress, 2018. [pdf]
• Richard French, Viktoriya Degeler and Kevin Jones. A Model of a Malware Infected Automated Guided Vehicle for Experimental Cyber-Physical Security, SAI Computing Conference, 2016. [pdf]
• V. Degeler, R. French and K. Jones, “Self-Healing Intrusion Detection System Concept,” 2016 IEEE 2nd International Conference on Big Data Security on Cloud (BigDataSecurity), IEEE International Conference on High Performance and Smart Computing (HPSC), and IEEE International Conference on Intelligent Data and Security (IDS), New York, NY, USA, pp. 351-356, 2016. doi: 10.1109/BigDataSecurity-HPSC-IDS.2016.27; [pdf]
• Viktoriya Degeler, Richard French and Kevin Jones. Combined Danger Signal and Anomaly-Based Threat Detection in Cyber-Physical Systems, In: Internet of Things. IoT Infrastructures. IoT360 2015. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 169. Springer, Cham, 2nd EAI International Conference on Safety and Security in Internet of Things (SaSeIoT), 2015. doi: 10.1007/978-3-319-47063-4_3; [pdf]
• Viktoriya Degeler, Richard French and Kevin Jones. Demonstrating Danger Theory Based Threat Detection for Robotic Manufacture Protection, SAI Intelligent Systems Conference (IntelliSys), 283–284, 2015. Best Demonstration Award.
• V. Degeler and A. Lazovik. Dynamic Constraint Satisfaction with Space Reduction in Smart Environments, International Journal on Artificial Intelligence Tools, 23(06), 2014. [pdf]
• Viktoriya Degeler. Dynamic Rule-Based Reasoning in Smart Environments, PhD thesis, University of Groningen, 2014. [pdf]
• V. Degeler and E. Curry. Human-Assisted Rule Satisfaction in Partially Observable Environments, In 2014 IEEE 11th Intl Conf on Ubiquitous Intelligence and Computing and 2014 IEEE 11th Intl Conf on Autonomic and Trusted Computing and 2014 IEEE 14th Intl Conf on Scalable Computing and Communications and Its Associated Workshops, Bali, Indonesia, pp. 171-178, 2014. doi: 10.1109/UIC-ATC-ScalCom.2014.134; [pdf]
• Edward Curry, Viktoriya Degeler, Eoghan Clifford, Daniel Coakley, Andrea Costa, Schalk-Jan Van Andel, Nick Van De Giesen, Christos Kouroupetroglou, Thomas Messervey, Jan Mink, Sander Smit, “Linked Water Data For Water Information Management”, In 11th International Conference on Hydroinformatics (HIC 2014), New York, New York, USA, 2014. [pdf]
• Eoghan Clifford, Daniel Coakley, Edward Curry, Viktoriya Degeler, Andrea Costa, Thomas Messervey, Schalk-Jan Van Andel, Nick Van de Giesen, Christos Kouroupetroglou, Jan Mink, Sander Smit. Interactive Water Services: The Waternomics Approach, In 16th international conference Water Distribution Systems Analysis (WDSA), Procedia Engineering, vol. 89, pp. 1058-1065, Elsevier, 2014. doi: 10.1109/10.1016/j.proeng.2014.11.225; [pdf]
• Viktoriya Degeler, Alexander Lazovik, Francesco Leotta, Massimo Mecella. Itemset-based Mining of Constraints for Enacting Smart Environments. 2014 IEEE International Conference on Pervasive Computing and Communication Workshops (PERCOM WORKSHOPS), Budapest, Hungary, pp. 41-46, 2014. doi: 10.1109/PerComW.2014.6815162; [pdf]
• V. Degeler and A. Lazovik. Architecture pattern for context-aware smart environments, “Creating Personal, Social and Urban Awareness through Pervasive Computing”, eds. D. Riboni, B. Guo, P. Hu, IGI Global, 2013. [pdf]
• V. Degeler, L. I. Lopera Gonzalez, M. Leva, P. Shrubsole, S. Bonomi, O. Amft, and A. Lazovik, Service-Oriented Architecture for Smart Environments, 2013 IEEE 6th International Conference on Service-Oriented Computing and Applications, Koloa, HI, USA, pp. 99-104, 2013. doi: 10.1109/SOCA.2013.26; [pdf]
• V. Degeler and A. Lazovik. Dynamic Constraint Reasoning in Smart Environments. 2013 IEEE 25th International Conference on Tools with Artificial Intelligence, Herndon, VA, USA, pp. 167-174, 2013. doi: 10.1109/ICTAI.2013.34; [pdf]. Best Student Paper Award.
• T. A. Nguyen, V. Degeler, R. Contarino, A. Lazovik, D. Bucur, and M. Aiello. Towards Context Consistency in a Rule-Based Activity Recognition Architecture. 2013 IEEE 10th International Conference on Ubiquitous Intelligence and Computing and 2013 IEEE 10th International Conference on Autonomic and Trusted Computing, Vietri sul Mare, Italy, pp. 625-630, 2013. doi: 10.1109/UIC-ATC.2013.97; [pdf]
• I. Georgievski, V. Degeler, G. A. Pagani, T. A. Nguyen, A. Lazovik, and M. Aiello. Optimizing Energy Costs for Offices Connected to the Smart Grid. In IEEE Transactions on Smart Grid, vol. 3, no. 4, pp. 2273-2285, 2012. doi: 10.1109/TSG.2012.2218666; [pdf]
• V. Degeler and A. Lazovik. Reduced Context Consistency Diagrams for Resolving Inconsistent Data. EAI Endorsed Trans. on Ubiquitous Environments, 12(10-12). doi: 10.4108/trans.ubienv.2012.10-12.e2; [pdf]
• F. Nizamic, V. Degeler, R. Groenboom, and A. Lazovik (2012) Policy-Based Scheduling of Cloud Services. Scalable Computing: Practice and Experience, 13(3):187-199. [pdf]
• V. Degeler and A. Lazovik. Cost-efficient Context-aware Rule Maintenance. 2012 IEEE International Conference on Pervasive Computing and Communications Workshops, Lugano, Switzerland, pp. 608-612, 2012. doi: 10.1109/PerComW.2012.6197587; [pdf]
• V. Degeler, and A. Lazovik. Interpretation of Inconsistencies via Context Consistency Diagrams. 2011 IEEE International Conference on Pervasive Computing and Communications (PerCom), Seattle, WA, USA, pp. 20-27, 2011. doi: 10.1109/PERCOM.2011.5767588; [pdf]
• I. Georgievski, V. Degeler, G. A. Pagani, T. A. Nguyen, A. Lazovik, and M. Aiello. Optimizing Offices for the Smart Grid. Technical Report JBI preprint 2011-12-01, University of Groningen, Nov 2011. [pdf]
• V. Degeler, I. Georgievski, A. Lazovik, and M. Aiello. Concept mapping for faster QoS-Aware Web Service Composition. 2010 IEEE International Conference on Service-Oriented Computing and Applications (SOCA), Perth, WA, Australia, pp. 1-4, 2010. doi: 10.1109/SOCA.2010.5707193; [pdf]. 1st place in Architectural challenge of Web Services Challenge’10