We study model reduction techniques for solving certain type of optimal control and sampling problems for diffusion processes. We propose two numerical algorithms for solving such problems. The algorithms combine model reduction techniques for studying multiscale dynamics and aim at reducing the problems to controlling the dynamics along either reaction coordinate or transition path, such that the “curse of dimensionality” can be alleviated. The effectiveness of our algorithms are demonstrated by numerical examples. This is a joint work with Carsten Hartmann and Christof Schuette.