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.
Publikasjoner og forskningsresultater
Vitenskapelige publikasjoner
Mian, Haris Hameed; Machot, Fadi Al; Ullah, Habib;
Keprate, Arvind
; Siddiqui, Muhammad Salman
(2025).
Advances in computational intelligence for floating offshore wind turbines aerodynamics: Current state review and future potential.
Renewable and Sustainable Energy Reviews.
Vol. 224.
https://doi.org/10.1016/j.rser.2025.116098
Kumar, Rohit; Prasad, Kala J.;
Keprate, Arvind
; Sen, Subhamoy
(2025).
Addressing material uncertainty in reliability analysis of floating offshore mooring through probabilistic meta-model developed with Stochastic Kriging technique.
Ocean Engineering.
Vol. 335.
https://doi.org/10.1016/j.oceaneng.2025.121697
Chauhan, Shivani; Solanki, Preeti; Putatunda, Chayanika; Walia, Abhishek;
Keprate, Arvind
; Bhatt, Arvind Kumar; Thakur, Vijay Kumar; Bhatia, Ravi Kant
(2025).
Recent advancements in biomass to bioenergy management and carbon capture through artificial intelligence integrated technologies to achieve carbon neutrality.
Sustainable Energy Technologies and Assessments.
Vol. 73.
https://doi.org/10.1016/j.seta.2024.104123
Kumar, Rohit; Sen, Subhamoy;
Keprate, Arvind
(2025).
Real-time fatigue assessment of Floating Offshore Wind Turbine Mooring employing sequence-to-sequence-based deep learning on indirect fatigue response.
Ocean Engineering.
Vol. 315.
https://doi.org/10.1016/j.oceaneng.2024.119741
Awan, Usama;
Keprate, Arvind
; Braathen, Petter
(2025).
A Conceptual Framework of An Integrative Leadership for Cybersecurity Management and Designing Digital Road Map for Organizations.
Behl, Abhishek; Sampat, Brinda (Red.).
Digital Transformation: A Business Imperative.
Routledge.
https://www-taylorfrancis-com.ezproxy.inn.no/chapt
Baniya, Jenish
;
Dai, Jian
; Jiang, Zhiyu; Zhang, Chi;
Keprate, Arvind
(2025).
Effect of Mooring Pretension Force
of a Soft-Connected Floating Photovoltaic
System Under Regular Waves.
Zhao, Xiao Lin; Dai, Jian-Guo; Liu, Siwei; Lim, Soon Heng (Red.).
Proceedings of the Fourth World Conference on Floating Solutions: WCFS 2024; 2–4 December; Hong Kong.
Springer Nature.
https://doi.org/10.1007/978-981-96-4569-5_35
Komulainen, Tiina M.
; Marsteng, Jansen Katrine;
Keprate, Arvind
(2024).
Analysing the Effect of Additional Instrumentation on Prediction of COD Removal in the Hias Process.
Lecture Notes in Civil Engineering.
Vol. 524.
https://doi.org/10.1007/978-3-031-63353-9_68
Siddiqui, Muhammad Salman; Waheed, Abdul Waheed; Yang, Liang; Saeed, Muhammed;
Keprate, Arvind
(2024).
Qualitative Investigation of Wake Composition in Offshore Wind Turbines: A Combined Computational and Statistical Analysis of Inner and Outer Blade Sections.
E3S Web of Conferences.
Vol. 487.
https://doi.org/10.1051/e3sconf/202448701001
Frafjord, Aksel Johan; Radicke, Jan-Philip;
Keprate, Arvind
;
Komulainen, Tiina
(2024).
Data-driven approaches for deriving a soft sensor in a district heating network.
Energy.
Vol. 292.
https://doi.org/10.1016/j.energy.2024.130426
Mian, Haris Hameed; Siddiqui, Muhammad Salman;
Keprate, Arvind
; Mathew, Sathyajith
(2024).
Predictive Modeling of Semi-Submersible Floater Motion Using Bi-LSTM Model.
Journal of Physics: Conference Series (JPCS).
Vol. 2875.
https://doi.org/10.1088/1742-6596/2875/1/012029
