Manoranjan Kumar | lnu.se

My research school

The industry graduate school Data Intensive Applications (DIA) Data Intensive Applications (DIA) is a graduate school for industrial doctoral students that focuses on applied research, addressing the…

My research groups

Data Intensive Software Technologies and Applications (DISTA) The research group Data Intensive Software Technologies and Applications studies data-driven approaches, such as machine learning,…
Linnaeus University Centre for Data Intensive Sciences and Applications The DISA research centre at Linnaeus University focuses its efforts on open questions in collection, analysis and utilization of…

My ongoing research projects

Doctoral project: Digital twin developments within Volvo CE This doctoral project relates to develop a so-called digital twin platform. The aim is to understand customers' problems and support them…

Publications

Article in journal (Refereed)

Ghanadi, M., Kumar, M., Danielsson, P., Hultgren, G., Barsoum, Z. (2025). Unsupervised machine learning for local stress identification in fatigue analysis of welded joints. Welding in the World. 69. 213-226.
Status: Published
Kumar, M., Ekevid, T., Löwe, W. (2024). Operator model for wheel loader short-cycle loading handling. Automation in Construction. 167.
Status: Published

Conference paper (Refereed)

Kumar, M., Löwe, W., Cramsky, J., Danielsson, P. (2023). Driving pattern classification for wheel loaders in different material handling using machine learning. IEEE Transactions on Intelligent Transportation Systems, ITSC. 283-290.
Kumar, M., Cramsky, J., Löwe, W., Danielsson, P. (2023). A prediction model for exhaust gas regeneration(EGR) clogging using offline and online machinelearning. Commercial Vehicle Technology 2022 : Proceedings of 7th commercial vehicle technology symposium.. 185-198.