Academic Career and Research Areas
The research of Prof. Ulbrich centers on nonlinear optimization and optimal control. He is particularly interested in the development and analysis of efficient algorithms for solving challenging large-scale nonlinear optimization problems. His research is often related to applications, e.g., in the context of shape optimization and control of fluid flows, parameter identification, or the analysis of human motion. Prof. Ulbrich is a PI in the DFG/FWF International Research Training Group IGDK 1754 and in the DFG Priority Program SPP 1962. He is an Associate Editor of several leading journals.
After studying mathematics, Prof. Ulbrich received his doctorate (1996) and his Habilitation (2002) at TUM. Funded by the DFG, he conducted research at Rice University, Houston, USA, in 1996/97 and 1999/2000. In 2002, he became a Full Professor at the University of Hamburg. Since 2006, Prof. Ulbrich has been a Full Professor at TUM, holding the Chair of Mathematical Optimization. From 2007 to 2010, he was Dean of Academic Affairs and 2012-2015 Vice Dean of the Department of Mathematics.
- Howard Rosenbrock Prize (2015)
- multiple awards as "Professor of the Semester" (University of Hamburg, 2002-2006)
- Dissertation Award of Bund der Freunde der TUM (1996)
Key Publications (alle Publikationen)
Milzarek, A, Ulbrich, M: "A semismooth Newton method with multi-dimensional filter globalization for l_1-optimization". SIAM Journal on Optimization. 2014; 24(1): 298-333.Abstract
Ulbrich, M: "Semismooth Newton methods for variational inequalities and constrained optimization problems in function spaces". MOS/SIAM Series on Optimization 11. Philadelphia: SIAM, 2011.Abstract
Steffensen S, Ulbrich M: "A new relaxation scheme for mathematical programs with equilibrium constraints". SIAM Journal on Optimization. 2010; 20(5): 2504-2539.Abstract
Hinze M, Pinnau R, Ulbrich M, Ulbrich S: Optimization with PDE constraints. New York, Springer-Verlag, 2009.Abstract
Ulbrich M, Ulbrich S, Vicente LN: "A globally convergent primal-dual interior-point filter method for nonlinear programming". Mathematical Programming. 2004; 100(2): 379-410.Abstract