Preprints

1. C. Geiersbach, J. Milz.
   Sample-based consistency in infinite-dimensional conic-constrained stochastic optimization.
   To appear in SIAM Journal on Optimization. [arXiv]
2. C. Geiersbach, T. Suchan, K. Welker.
   Optimization of piecewise smooth shapes under uncertainty using the example of Navier-Stokes flow.
   Submitted (2023). [WIAS Preprint] [arXiv]

Articles in Journals

1. P. Dvurechensky, C. Geiersbach, M. Hintermüller, A. Kannan, S. Kater, G. Zöttl.
   A Cournot-Nash model for a coupled hydrogen and electricity market.
   Energy Systems (2026). [Open access]
2. M. Dambrine, C. Geiersbach, H. Harbrecht.
   Two-norm discrepancy and convergence of the stochastic gradient method with application to shape optimization.
   SIAM Journal on Optimization (2026). [arXiv]
3. A. Alphonse, C. Geiersbach, M. Hintermüller, T. Surowiec.
   Risk-averse optimal control of random elliptic variational inequalities.
   ESAIM: Control, Optimisation and Calculus of Variations (ESAIM: COCV): 31 (2025) 71. [Open access]
4. C. Geiersbach, R. Henrion, P. Pérez-Aros.
   Numerical solution of an optimal control problem with probabilistic and almost sure state constraints.
   Journal of Optimization Theory and Applications (2024). [Open access]
5. C. Geiersbach, T. Suchan, K. Welker.
   Stochastic augmented Lagrangian method in shape spaces.
   Journal of Optimization Theory and Applications (2024). [Open access]
6. C. Geiersbach, R. Henrion.
   Optimality conditions in control problems with random state constraints in probabilistic or almost-sure form.
   Mathematics of Operations Research (2024). [WIAS Preprint] [arXiv]
7. C. Geiersbach, T. Scarinci.
   A stochastic gradient method for a class of nonlinear PDE-constrained optimal control problems under uncertainty.
   Journal of Differential Equations 364 (2023) 635-666. [arXiv]
8. C. Geiersbach, M. Hintermüller.
   Optimality conditions and Moreau-Yosida regularization for almost sure state constraints.
   ESAIM: Control, Optimisation and Calculus of Variations (ESAIM: COCV): 28 (2022) 80. [Open access]
9. C. Geiersbach, W. Wollner.
   Optimality conditions for convex stochastic optimization problems in Banach spaces with almost sure state constraints.
   SIAM Journal on Optimization 31(4): 2455-2480 (2021). [WIAS Preprint] [arXiv]
10. C. Geiersbach, E. Loayza-Romero, K. Welker.
    Stochastic approximation for optimization in shape spaces.
    SIAM Journal on Optimization 31(1): 348-376 (2021). [arXiv]
11. C. Geiersbach, T. Scarinci.
    Stochastic proximal gradient methods for nonconvex problems in Hilbert spaces.
    Computational Optimization and Applications (2021). [Open access]
12. C. Geiersbach, W. Wollner.
    A stochastic gradient method with mesh refinement for PDE constrained optimization under uncertainty.
    SIAM Journal on Scientific Computing 42(5): A2750--A2772 (2020). [arXiv]
13. C. Geiersbach, G. Pflug.
    Projected stochastic gradients for convex constrained problems in Hilbert spaces.
    SIAM Journal on Optimization 29(3): 2079-2099 (2019). [arXiv]
14. C. Geiersbach, C. Heitzinger, G. Tulzer.
    Optimal approximation of the first-order corrector in multiscale stochastic elliptic PDE.
    SIAM/ASA Journal on Uncertainty Quantification 4(1): 1246-1262 (2016).

Book Chapters

1. C. Geiersbach, E. Loayza-Romero, K. Welker.
   PDE-constrained shape optimization: towards product shape spaces and stochastic models.
   Chen, K.; Schönlieb, C.-B.; Tai, X.-C. & Younces, L. (Eds.) Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging: Mathematical Imaging and Vision, Springer International Publishing, 2022, 1-46. [Online-first] [arXiv]

Software

N. Angleitner, C. Geiersbach, C. Heitzinger, G.Tulzer.
EllipticFEM.jl -- a FEM Solver for Elliptic, Parabolic and Hyperbolic PDEs, in the Julia programming language. (not maintained)

Selected Talks

WCCM ECCOMAS 2026, Advances in PDE-constrained Optimization I section
7.2026 ♦ Munich, Germany

IPMS 2026, Bayesian, Variational, and Stochastic Methods for Uncertainty Quantification session
6.2026 ♦ Malta

XVII ICSP 2025, Chance constraints in optimal control section
7.2025 ♦ Champs-sur-Marne, France

ICCOPT 2025, Recent Advances in PDE-Constrained Optimization session
7.2025 ♦ Los Angeles, CA, USA

16th Viennese Conference on Optimal Control and Dynamic Games, Uncertainty quantification in optimization, optimal control, and identification minisymposium
7.2025 ♦ Vienna, Austria

Oberwolfach workshop Uncertainty quantification
4.2025 ♦ Oberwolfach, Germany

Oberwolfach workshop Data-driven modeling, analysis, and control of dynamical systems
12.2024 ♦ Oberwolfach, Germany

PGMO Days 2024, Shape optimization and optimal control section
11.2024 ♦ Paris-Saclay, France

25th International Symposium on Mathematical Programming (ISMP), PDE-constrained optimization under uncertainty section
7.2024 ♦ Montreal, Canada

SIAM Conference on Uncertainty Quantification (UQ24), Efficient solution schemes for optimization of complex systems under uncertainty section
2.2024 ♦ Trieste, Italy

XVI ICSP 2023, Advances of stochastic dominance theory and applications section
7.2023 ♦ Davis, CA, USA

PGMO Days 2022, New developments in optimal control theory section
11.2022 ♦ Paris-Saclay, France

GAMM 2022, Optimization of differential equations section (keynote presentation)
8.2022 ♦ Aachen, Germany

ICCOPT 2022, PDE Constrained Optimization with Nonsmooth Structures session
7.2022 ♦ Bethlehem, PA, USA

15th Viennese Conference on Optimal Control and Dynamic Games, Continuous optimization: theory and applications minisymposium
7.2022 ♦ Vienna, Austria

SIAM Conference on Uncertainty Quantification (UQ22), PDE-Constrained Optimization Under Uncertainty minisymposium
4.2022 ♦ Virtual

SIAM Conference on Imaging Science (IS22), Stochastic Iterative Methods for Inverse Problems minisymposium
3.2022 ♦ Virtual

15th International Conference on Free Boundary Problems: Theory and Applications, UQ in free boundary problems session
9.2021 ♦ Virtual

International Conference on Spectral and High Order Methods, Shape and topology optimization session
7.2021 ♦ Virtual

SIAM Conference on Computational Science and Engineering, Risk-averse PDE-constrained optimization session
3.2021 ♦ Virtual

Oberwolfach workshop Challenges in optimization with complex PDE-systems
2.2021 ♦ Virtual

WIAS workshop PDE constrained optimization under uncertainty and mean field games
1.2020 ♦ Berlin, Germany

Konstanz Workshop on Optimal Control
12.2019 ♦ Konstanz, Germany

International Conference on Stochastic Programming XV
7.2019 ♦ Trondheim, Norway

International Congress on Industrial and Applied Mathematics
7.2019 ♦ Valencia, Spain

Workshop: modelling and simulation in science in KAUST
2.2019 ♦ Thuwal, Saudi Arabia

GAMM 2019
2.2019 ♦ Vienna, Austria

Oberwolfach workshop Surface, bulk, and geometric partial differential equations: interfacial, stochastic, non-local and discrete structures
1.2019 ♦ Oberwolfach, Germany

4th Central European Set-Valued and Variational Analysis Meeting
11.2018 ♦ Marburg, Germany

5th European Conference on Computational Optimisation
9.2018 ♦ Trier, Germany

Oberwolfach workshop New Directions in Stochastic Optimization
8.2018 ♦ Oberwolfach, Germany

Women in Shape 3: Modeling Objects in 2D and 3D workshop
7.2018 ♦ Trier, Germany

14th Viennese Conference on Optimal Control and Dynamic Games
7.2018 ♦ Vienna, Austria

European Conference on Stochastic Optimization
9.2017 ♦ Rome, Italy