Joel Cramsky | lnu.se

Master in engineering physics at LTH
R&D engineer at Volvo CE in Braås
Industrial Phd candidate at LNU within the DIA program
Interested in topics related to digital twins

Contact: joel.cramsky.2@volvo.com

Research

https://lnu.se/en/research/searchresearch/research-projects/doctoral-project-digital-twin-developments-within-volvo-ce/

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

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.