Christian Offen, PhD, Massey University, New Zealand

Numerical Mathematics and Control


Office Address:
Technologiepark 21
33100 Paderborn

About Christian Offen

Curriculum Vitae

08/2020 - 10/2024: Postdoc

Paderborn University, Department of Mathematics. Research Group Applied Mathematics, Numerics, and Optimization. Member of MKW NRW Projekt Photonisches Quantencomputing (PhoQC)

11/2016 - 09/2020: PhD in Mathematics

Massey University, New Zealand. Thesis: Analysis of Hamiltonian boundary value problems and symplectic integration, advisor: Dist. Prof. Robert McLachlan. (2019 - Hatherton Award,   2020 - Dean's List of Exceptional Theses)

10/2014 - 09/2016: Master of Science Mathematics

University of Hamburg, Master studies. Thesis: Seiberg-Witten Curves and Parabolic Affine Spheres (Differential Geometry), advisor: Prof. Dr. Vicente Cortés

10/2011 - 09/2014: Bachelor of Science Mathematics

University of Hamburg, Bachelor studies. Thesis: Classification of solutions of the Monge-Ampère equation in the finitely punctured plane (Differential Geometry), advisor: Prof. Dr. Vicente Cortés

21.08.2020: Thesis Award

Honour of inclusion of my doctoral thesis in the Dean’s List of Exceptional Doctoral Theses

17.10.2019: Hatherton Award 2019

Best scientific paper by a PhD student at any New Zealand university in chemical sciences, physical sciences, mathematical and information sciences - Royal Society of New Zealand (Hatherton Award 2019)

06.12.2017: Aitken Prize (Honorary mention)

Honorary mention in the Aitken Prize of the New Zealand Mathematical Society for the talk "Bifurcations of solutions to Hamiltonian boundary value problems"

01.05.2014: German Academic Scholarship Foundation

Award of a scholarship by the German Academic Scholarship Foundation (Studienstiftung des deutschen Volkes)

17.05.2011: Award by the German Mathematical Society (Abiturpreis)

Award for outstanding highschool graduates by the German Mathematical Society


Research Interests

  • Structure-preserving numerical integration
  • Data-driven models for dynamical systems (especially Hamiltonian/Lagrangian systems)
  • Kernel-based methods
  • Multi-symplectic integration
  • Lie group methods
  • Bifurcation theory