Calendar

Posted September 21, 2026
Last modified November 3, 2026

Control and Optimization Seminar Questions or comments?

Radu Bot, University of Vienna
Continuous- and Discrete-Time Methods in Convex Optimization and Monotone Inclusions

In this talk, we explore the interplay between continuous-time and discrete-time models for solving convex optimization problems and monotone inclusions. We discuss strategies for achieving faster convergence rates across the different settings, as well as issues related to the convergence of trajectories and iterates.

Posted September 22, 2026
Last modified November 6, 2026

Control and Optimization Seminar Questions or comments?

Rene Henrion, Weierstrass Institute for Applied Analysis and Stochastics, Germany
Chance Constraints in Optimal Control

Chance constraints represent a major tool in stochastic optimization for dealing with random inequality constraints. They allow one to find optimal decisions satisfying the inequality constraints with high probability. Introduced originally in the context of operations research (finite dimensional optimization) with applications among others to water reservoir mangement, capacity expansion in electrical networks or blending problems, they have recently attracted much attention in optimal control, in particular in risk-averse PDE-constrained optimization or in the optimal control of sweeping processes with randomly perturbed control. The talk addresses applications theoretical results (optimality conditions, existence of solutions) as well as algorithmic aspects (spherical-radial decomposition of Gaussian random vectors) related with chance constraints in optimal control.

Posted September 1, 2026

Control and Optimization Seminar Questions or comments?

Jun Liu, University of Waterloo, Canada
TBA