Bjarne André Grimstad

Bjarne André Grimstad is an Associate Professor at the Norwegian University of Science and Technology (NTNU). His work focuses on optimization, surrogate modeling, and data-driven approaches for complex systems in chemical and petroleum engineering. Key contributions include advancements in B-spline models, hybrid gray-box systems, and neural network applications for virtual flow metering.

Research interests span optimization algorithms, machine learning integration with physical models, and industrial process control. Notable publications address multi-task learning frameworks, identifiability in hybrid models, and the efficacy of gray-box modeling in nonstationary environments.

Publications (2024–2015) highlight interdisciplinary work combining mathematical programming with real-world applications in oil & gas production and flow measurement. His 2015 doctoral dissertation explored daily production optimization using surrogate modeling techniques.

Outreach activities include academic lectures at international conferences (e.g., IFAC OOGP 2015) and poster presentations on hybrid modeling at Geilo Winter School 2021. Collaborations with industry partners like SINTEF and TU Delft underscore his applied research focus.