Kort om
Dr. Arvind Keprate received his B.Tech in Mechanical Engineering (2007) from Himachal Pradesh University, M.Sc. in Marine & Subsea Technology (2014), and Ph.D. (2017), in Offshore Engineering from the University of Stavanger, Norway. During his Ph.D. he was a visiting researcher at the Prognostics Center of Excellence, NASA Ames Research Center, USA, where he developed a surrogate model (using machine learning and deep learning) to predict the stress intensity factor (SIF) for various crack sizes and loading conditions.
He is currently a Professor at Oslo Metropolitan University where he teaches various Design-related courses such as Machine Design, Process & Piping Design, and Sustainable Design to Mechanical Engineering students. He also teaches various courses related to Machine Learning, Probability & Statistics, Data Analytics, and Python at Kristiania University College in Oslo. He is also the Leader of the Mechanics, Mechatronics, and Materials Technology (M3T) Research Group at OsloMet and also the Project Manager for the GrønnMet lab. Besides this, he is also a member of the Doctoral Committee at the faculty.
Dr. Keprate has over 10 years of industrial experience (Reliance Industries Limited, DNV) as a pipeline engineer, with expertise in fatigue analysis, fitness-for-service (FFS) assessment, asset integrity, and risk/reliability engineering. He is also an accomplished researcher specializing in the application of machine learning and probabilistic techniques to Condition Monitoring, Prognostics, Reliability Modelling, and Integrity Assessment of engineering assets. Currently, his research is focused on PHM of complex Socio-Ecological Technical Systems such as Wind Farms.
Dr. Keprate has been awarded research grants from funding agencies, including the Research Council of Norway (RCN), Norwegian Directorate for Higher Education and Skills (HK-dir), Norwegian AI Research Consortium (NORA), and RegionaleForskningFond (RFF).
Dr. Keprate also serves as an Associate Editor for the International Journal of System Assurance Engineering and Management, Springer-Nature, and has been a topic editor for a Special Issue on “Online Monitoring of Wind Power Plants Using Digital TwinModels”, Frontiers in Energy Research.
