  Over the last ten years, we have seen a significant increase in industrial
data, tremendous improvement in computational power, and major theoretical
advances in machine learning. This opens up an opportunity to use modern
machine learning tools on large-scale nonlinear monitoring and control
problems. This article provides a survey of recent results with applications in
the process industry.
