MODUS Seminar Program

Weekly talks in the MODUS Seminar: Wednesday, 12:30-14:00, Room S102, FAN-B
Individual talks may be held via zoom or at different times, see the information, below.

Further talks will be announced as the semester progresses. To receive email notifications about upcoming talks, please subscribe to the MODUS elearning course.

Winter Semester 2026/2027

Friday, 9 October 2026, 10:00h, Room S 82 (NW II)
Sébastien Gros
Professor, Department of Engineering Cybernetics, NTNU Trondheim, Norway
Combining Reinforcement Learning and MPC - How to take optimal decisions with wrong models?

Abstract: Reinforcement Learning (RL) can be used to tune MPC schemes towards closed-loop optimality in the real world. That tuning is fundamentally different than using classical fitting approaches to adjust the model underlying MPC. These ideas are supported by a rich theory on how MPC is a universal approximation for Markov Decision Processes, provided that it is viewed in the right way. That theory proposes a bridge between the open-loop predictions of MPC and its closed-loop implementation. It also explains why using classical model fitting is sometimes good enough for achieving near-optimal closed-loop performance with MPC, and why it often falls short of achieving that. It finally opens a theoretical pathway on using (imperfect) simulation models to build optimal policies for the real-world, and on closing the “sim2real gap”. In this talk, we will provide an overview of these recent advances.

28 October 2026, 12:30h
Jonathan Schmalfuß
PhD Student, Chair of Scientific Computing, Universität Bayreuth
Mesh Partitioning with Explicit Communication Constraints

Abstract: Motivated by applications demand that existing tools could not support, we propose a method for enforcing explicit constraints on a partition’s quotient graph. At the coarsest level of multilevel k-way partitioning, we use several integer linear programming models to bound the graph’s maximum degree, constrain connectivity among groups of subdomains, or match a given reference quotient graph. We present models with linear complexity and investigate additional heuristics. Finally, we show that these constraints improve the performance of a shallow water solver.

11 November 2026, 12:30h
Jörg Rambau
Professor und Leiter des Lehrstuhls für Wirtschaftsmathematik, Universität Bayreuth
Title will be announced later

25 November 2026, 12:30h
Alberto de Marchi
Research Assistant, Engineering Mathematics, Universität der Bundeswehr München
Quadratic Optimization with Geometric Constraints: From Theory to Robot Control and Asset Allocation

Abstract: Many problems in optimization, control, and robotics involve convex quadratic costs subject to geometric constraints: sets with structured nonconvexity arising from logical conditions, cardinality restrictions, or physical complementarity relations. Model-based control of rigid and soft robots with frictional contacts can be formulated as quadratic programs with conic complementarity constraints, induced by the Signorini condition, Coulomb friction, and maximum dissipation. Likewise, the classical portfolio optimization problem, extended with minimum buy-in constraints, cardinality costs, or logical coupling conditions, leads to quadratic programs with the same geometric structure.
This talk presents two approaches to this challenging problem class, both built on the augmented Lagrangian framework combined with projections onto such structured nonconvex sets. By exploiting the underlying linear-quadratic structure, the two strategies aim to accelerate the augmented Lagrangian subproblem solves while preserving global convergence guarantees.
References: De Marchi, "A condensing approach for linear-quadratic optimization with geometric constraints" (2026), presented at ECC26
Ménager, Fabre, Bambade, Jallet, De Marchi, Carpentier, "Frictional contact-implicit inverse dynamics" (2025), submitted to IEEE T-RO.

9 December 2026, 12:30h
Boris Wembe Moafo
Research Associate, Numerical Mathematics and Control, Universität Paderborn
Title will be announced later

Further talks will be announced until the end of October 2026