Bjarne André Grimstad

Bjarne André Grimstad is an Associate Professor at the Norwegian University of Science and Technology (NTNU). His work focuses on virtual flow metering, surrogate modeling, and optimization of industrial systems. He has extensively explored hybrid modeling approaches combining data-driven and mechanistic methods, particularly through B-spline constraints and neural networks. His research spans mathematical programming, multi-task learning, and adaptive observer designs for gas-lift wells.

His publications highlight advancements in virtual flow metering, including Bayesian neural networks, gray-box modeling, and nonstationarity handling. Key collaborations include Lars Struen Imsland, Odd Kolbjørnsen, and Bjarne Anton Foss. While no specific educational details are provided, his 2015 PhD thesis at NTNU established the foundation for his work in surrogate modeling and production optimization.

Grimstad’s work trends involve integrating machine learning with industrial control systems, emphasizing practical applications in petroleum production. He has contributed to methods using B-splines for global optimization and divide-and-conquer strategies in production systems. Despite numerous publications, no scientific awards or student advising details are mentioned in the available text.