He graduated from the Universiteit van Amsterdam (UvA, the Netherlands). His current research group uses optimality principles, Bayesian statistics, Monte Carlo simulation and evolutionary strategies to better analyze the mismatch between models and data and help improve theory, understanding and predictability of environmental systems. He regularly develops new methods and uses parallel computing to solve the most complex and computationally demanding (inverse) problems. He draws inspiration from emerging model-data synthesis problems in surface hydrology, soil physics, hydrogeophysics, and hydrometeorology.