Assistant Professor of Mathematics (Optimization under Uncertainty)
at the University of Hamburg
The focus of my research is in stochastic optimization and algorithms over possibly infinite-dimensional spaces.
Stochastic optimization
- Problems formulated over function or shape spaces with uncertainties
- Nonsmooth problems and regularization techniques
- Stochastic generalized Nash equilibrium problems
- Applications, including in energy and shape optimization, to problems constrained by partial differential equations
Algorithms
- Projected and proximal stochastic gradient methods
- Convergence theory
- Numerical error associated with discretization
News
New preprint: A Cournot-Nash Model for a coupled hydrogen and electricity market [29. October 2024]
I have relocated from the Weierstrass Institute to the University of Hamburg! [1. October 2024]
New publication in Journal of Optimization Theory and Applications: Stochastic augmented Lagrangian method in Riemannian shape manifolds [21. August 2024]
New preprint: Two-norm discrepancy and convergence of the stochastic gradient method with application to shape optimization [12. August 2024]
New preprint: Numerical solution of an optimal control problem with probabilistic and almost sure state constraints [28. November 2023]
New preprint: Optimization of piecewise smooth shapes under uncertainty using the example of Navier-Stokes flow [15. August 2023]