Jacob Nilsson
Cyber-Physical Systems
Embedded Intelligent Systems LAB
Department of Computer Science, Electrical and Space Engineering
Research
My research focuses on enabling interoperability in systems of systems, specifically dynamic interoperability of messages, sometimes called semantic interoperability. I am currently investigating the approaches to combine modern machine learning techniques with metadata.
Current Projects
Past Projects
Teaching
- TA in Electric Circuit Theory (E0003E).
- TA in IoT-based industrial automation and digitalization (D7042E).
Other
Member of the board of the PhD Association 2020-2021 as a member of the Research Education Group.
Contact me
- My LinkedIn
Publications
Data set
JSON Dataset of Simulated Building Heat Control for System of Systems Interoperability (2022)
Doctoral thesis, comprehensive summary
Machine Learning Concepts for Service Data Interoperability (2022)
Part of: JSON Dataset of Simulated Building Heat Control for System of Systems Interoperability
Conference paper
Autoencoder Alignment Approach to Run-Time Interoperability for System of Systems Engineering (2020)
Part of: IEEE 24th International Conference on Intelligent Engineering Systems, Proceedings, s. 139-144, IEEE, 2020
Conference paper
Interoperability and machine-to-machine translation model with mappings to machine learning tasks (2019)
Part of: 2019 IEEE 17th International Conference on Industrial Informatics (INDIN), s. 284-289, IEEE, 2019
Conference paper
Interoperability automation considered as machine learning tasks (2019)
Paper presented at : 2nd Productive4.0 Consortium Conference, 12-14 March, 2019, Budapest, Hungary
Licentiate thesis, comprehensive summary
System of Systems Interoperability Machine Learning Model (2019)
Conference paper
Semantic Interoperability in Industry 4.0 (2018)
Survey of Recent Developments and Outlook
Part of: 2018 IEEE 16th International Conference on Industrial Informatics (INDIN), s. 127-132, IEEE, 2018, 8471971
Manuscript (preprint)
Machine Learning based System–of–Systems Interoperability
A SenML–JSON Case Study