Dr. rer. nat. Michael Obersteiner

Technische Universität München

Institut für Informatik
Boltzmannstrasse 3
85748 Garching

Office: MI 02.05.053
Mail: oberstei (at) in.tum.de 

Tel: +49-89-289-18603
Fax: +49-89-289-18607
Office Hours: by arrangement



  • Started stuides in Biochemistry in 2010
  • Switched to Computer Science in 2011 and finished M.Sc. in 2016
  • Currently working on my dissertation in Computer Science with a focus on high dimensional numerics and the Sparse Grid Combination Technique

Research interests

  • Molecular Dynamics
  • HPC
  • Combination technique
  • Sparse Grids Methods
  • Machine Learning


DisCoTec (distributed Combination Technique):

A C++ code that targets exascale computing with the Combination Technique for time-dependent PDEs. It was created in the course of the EXAHD project founded by the DFT and was part of SPPEXA. The code is parallelized via MPI and offers massively parallel execution of PDEs with arbitrary black box solvers that are provided by the user and integrated via adapters. The code is open-source and can be found on Github:


sparseSpACE (the Sparse Grid spatially adaptive combination environment):

A python code that implements the spatially adaptive variants of the Combination Technique developed during my disseration. It is designed to support arbitrary operations on the generated grids so that it potentially targets all Sparse Grid and Combination Technique applications. Currently there are implementations for numerical integration and interpolation, Uncertainty Quantification, Machine Learning with Density Estimation and PDE simulations. The code is open-source and published on Github:




  • Übungsleitung Algorithms for Scientific Computing SS18, SS19
  • Übungsleitung Numerisches Programmieren SoSe 2017, WiSe 2017/18, WiSe 2018/2019, WiSe 2019/2020
  • Tutor Diskrete Strukturen, WiSe 2016/2017

Tutor for many years in Numerical Programming

Open and Running Student Projects

Open Hiwi Positions

Open Student Projects

see: https://www5.in.tum.de/wiki/index.php/Projects_in_Sparse_Grids_and_High_Dimensional_Approximation

You can also come to my office and discuss possible topics.

Running Student Projects

  • P. Resch: Adaptive Romberg-Quadrature for the Sparse Grid Combination Technique, Bachelor's Thesis, Fakultät für Informatik, Informatics, since May 2020

Finished Student Projects


  • Markus Englberger: Using the Spatially Adaptive Combination Technique for Efficient Quantification of Uncertainty in Hydrological Models. Bachelorarbeit, 2022 mehr… BibTeX Volltext (mediaTUM)




  • Hendrik Möller: Dimension-wise Spatial-adaptive Refinement with the Sparse Grid Combination Technique. Bachelorarbeit, 2018 mehr… BibTeX Volltext (mediaTUM)
  • Philipp Zetterer: Investigation of Cluster Analysis Algorithms Using Radio Measurement Data of Public Mobile Networks. Masterarbeit, 2018 mehr… BibTeX
  • Thomas Bellebaum: Evaluation of different time-synchronization schemes for the combination technique. Bachelorarbeit, 2018 mehr… BibTeX Volltext (mediaTUM)



  • Michael Obersteiner; Hans-Joachim Bungartz: A Spatially Adaptive Sparse Grid Combination Technique for Numerical Quadrature. Sparse Grids and Applications - Munich 2018, 2022, 161-185 mehr… BibTeX Volltext ( DOI )


  • Obersteiner, Michael; Bungartz, Hans-Joachim: A Generalized Spatially Adaptive Sparse Grid Combination Technique with Dimension-wise Refinement. SIAM Journal on Scientific Computing 43 (4), 2021, A2381-A2403 mehr… BibTeX Volltext ( DOI )


  • Rafael Lago; Michael Obersteiner; Theresa Pollinger; Johannes Rentrop; Hans-Joachim Bungartz; Tilman Dannert; Michael Griebel; Frank Jenko; Dirk Pflüger: EXAHD: A Massively Parallel FaultTolerant Sparse Grid Approach for High-Dimensional Turbulent Plasma Simulations. In: Hans-Joachim Bungartz, Severin Reiz; Benjamin Uekermann; Philipp Neumann; Wolfgang E. Nagel (Hrsg.): Software for Exascale Computing - SPPEXA 2016-2019. Springer, 2020, 301-329 mehr… BibTeX Volltext ( DOI )


  • Michael Obersteiner, Hans-Joachim Bungartz: A Spatially Adaptive Sparse Grid Combination Technique for Numerical Quadrature. Sparse Grids and Applications - Munich 2018, Springer Verlag, 2019 mehr… BibTeX


  • Heene, Mario; Parra Hinojosa, Alfredo; Obersteiner, Michael; Bungartz, Hans-Joachim; Pflüger, Dirk: EXAHD: An Exa-Scalable Two-Level Sparse Grid Approach for Higher-Dimensional Problems in Plasma Physics and Beyond. In: Nagel, Wolfgang; Kröner, Dietmar; Resch, Michael (Hrsg.): High Performance Computing in Science and Engineering ' 17. Springer-Verlag, 2018 mehr… BibTeX


  • Obersteiner, Michael; Parra Hinojosa, Alfredo; Heene, Mario; Bungartz, Hans-Joachim; Pflüger, Dirk: A Highly Scalable, Algorithm-Based Fault-Tolerant Solver for Gyrokinetic Plasma Simulations. ScalA '17: Proceedings of the 8th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, 2017 mehr… BibTeX
  • Tchipev, Nikola; Gallard, Jean-Matthieu; Gratl, Fabio; Obersteiner, Michael; Neumann, Philipp; Bungartz, Hans-Joachim: A Highly Optimized Implementation of the Fast Multipole Method within the Molecular Dynamics Code ls1-mardyn – 4th International Conference on Computational Engineering (ICCE 2017). 2017, mehr… BibTeX





  • Michael Obersteiner: A Spatially Adaptive Sparse Grid Combination Technique. (Vortrag / Chair Meeting) 2019 mehr…


  • Obersteiner, Michael; Tchipev, Nikola; Neumann, Philipp; Bungartz, Hans-Joachim: A highly scalable MPI parallelization of the Fast Multipole Method. (Vortrag) 2017 mehr…



  • Ivana Jovanovic Buha; Michael Obersteiner; Tobias Neckel; Hans-Joachim Bungartz: Efficient Uncertainty Quantification and Global Time-Varying Sensitivity Analysis Using the Spatially Adaptive Combination Technique. SIAM Conference on Uncertainty Quantification (UQ22), SIAM, 2022Atlanta, Georgia mehr…