Erkan Karabulut (e.karabulut@uva.nl)
PhD Student, University of Amsterdam
Biography
I am a doctoral researcher at INDElab, University of Amsterdam, advised by Dr. Victoria Degeler and Prof. Dr. Paul Groth.
My research focuses on interpretable decision-making through Neurosymbolic knowledge discovery and inference, applied to Digital Twins and medical datasets.
I hold an MSc in Computer Science from TU Munich and a BSc in Computer Engineering from Yildiz
Technical University, Istanbul
.
Previously, I was a research assistant at
fortiss
and worked as a software engineer and consultant.
I am open to academic and non-academic collaborations -- feel free to reach out: e.karabulut@uva.nl
Recent Activities
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April 2025 - At NWO ICT.Open 2025 (15-16 April), I will be presenting our poster entitled Interpretable Decision-Making in Smart Environments.
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December 2024 - A new preprint (continuation of AE SemRL) entitled Learning Semantic Association Rules from Internet of Things Data is out on arXiv.
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November 2024 - I presented our paper entitled 3K: Knowledge-Enriched Digital Twin Framework at the LongevIoT’24 workshop as part of the ACM IoT 2024 conference.
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October 2024 - Our paper entitled DiTEC: Digital Twin for Evolutionary Changes in Water Distribution Networks is published at the International Symposium on Leveraging Applications of Formal Methods.
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June 2024 - I will be joining the International Semantic Web Research Summer School in Italy.
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March 2024 - A new preprint entitled "AE SemRL: Learning Semantic Association Rules with Autoencoders" is out on arXiv.
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February 2024 - I will be attending the "Masterclass on Data Semantics" seminar organized by SIKS.
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February 2024 - I have published a new blog post entitled Scribbles around the first year as a PhD student.
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January 2024 - I reviewed a submission for the Journal of Machine Learning Research.
Publications
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2024 - Karabulut, Erkan, Paul Groth, and Victoria Degeler. "Learning Semantic Association Rules from Internet of Things Data." arXiv preprint arXiv:2412.03417 (2024).
Link.
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2024 - Karabulut, Erkan, Paul Groth, and Victoria Degeler. "3K: Knowledge-Enriched Digital Twin Framework." (2024). In LongevIoT’24: 1st International Workshop on Longevity in IoT Systems, co-located with 14th International Conference on Internet of Things, November 19–22, 2024, Oulu, Finland.
Link.
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2024 - Degeler, Victoria, et al. "DiTEC: Digital twin for evolutionary changes in water distribution networks." International Symposium on Leveraging Applications of Formal Methods. Cham: Springer Nature Switzerland, 2024.
Link.
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2024 - Huang, Yiwen, Erkan Karabulut, and Victoria Degeler. "Large Language Model for Ontology Learning In Drinking Water Distribution Network Domain.". ELMKE’24: Evaluation of Language Models in Knowledge Engineering, co-located with 24th International Conference on Knowledge Engineering and Knowledge Management, 26-28 November, 2024, Amsterdam, The Netherlands.
Link.
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2024 - Erkan Karabulut, Victoria Degeler, and Paul Groth. AE SemRL: Learning Semantic Association Rules with Autoencoders, 2024.
Link.
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2023 - Karabulut, Erkan, Degeler, Victoria, and Groth, Paul. "Semantic Association Rule Learning from Time Series Data and Knowledge Graphs." In SemIIM’23: 2nd International Workshop on Semantic Industrial Information Modelling co-located with 22nd International Semantic Web Conference (ISWC 2023).
Link.
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2023 - Karabulut, Erkan, Salvatore F. Pileggi, Paul Groth, and Victoria Degeler. "Ontologies in digital twins: A systematic literature review." Future Generation Computer Systems (2023).
Link.
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2023 - E. Karabulut and R. C. Sofia, "An Analysis of Machine Learning-based Semantic Matchmaking," in IEEE Access, doi: 10.1109/ACCESS.2023.3259360. 2023.
Link.
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2022 - Bnouhanna, N., Karabulut, E., Sofia, R. C., Seder, E. E., Scivoletto, G., & Insolvibile, G. (2022, March). An Evaluation of a Semantic Thing To Service Matching Approach in Industrial IoT Environments. In 2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops) (pp. 433-438). IEEE.
Link.
Theses
- MSc. Thesis: ML-based Data Classification and Data Aggregation on the Edge. May 2022. Supervisors: Prof. Dr. Rute C. Sofia, Prof. Dr.-Ing. Jörg Ott.
- BSc. Thesis: Adaptive Learning-based Tracing Tool for Weather Research and Forecasting Software. January 2019. Supervisor: Assoc. Prof. Dr. Mehmet S. Aktaş