Sjoerd Boersma

Sjoerd Boersma is a Researcher at Biometris, Wageningen University & Research (WUR), specializing in the integration of advanced control systems with agricultural technology. His work focuses on developing predictive control models, observability analysis frameworks, and digital twin solutions to optimize greenhouse production, wind farm efficiency, and water resource management.

His research spans Control Theory, Agricultural Engineering, and Machine Learning, with specific expertise in predictive control for systems with parametric uncertainty, sensor configuration optimization, and Bayesian neural methods for crop modeling. Current projects address autonomous greenhouse control using reinforcement learning and virtual crop modeling for tomato production.

Recent publications reveal a strong trend toward cross-disciplinary solutions where digital twin technology bridges agricultural engineering and control systems. His work consistently targets sustainability challenges, from wind farm load reduction to precision water management and greenhouse climate optimization, demonstrating methodological innovation in applying control theory to biological systems.

Boersma actively mentors PhD candidates, serving as co-promotor for van Laatum, B.'s research on autonomous greenhouse control systems. His current projects include the active Autonomous Production Control of Greenhouse Farming System with Reinforcement Learning and the recently completed Virtual Tomato Crops initiative funded by WUR.

As a core member of the Biometris research group, he contributes to WUR's mission through collaborative projects like the VIOLA potato stress classification model and the digital twin framework for water management, emphasizing real-world implementation of control systems in agricultural environments.