Projects

• DFG project “ICEBAY – Temperature reconstruction combining boreholes thermometry and ice-cores with Bayesian hierarchical modelling – Global warming vs. natural variability in DML, Antarctica” (duration: 2026-2028)
  Research project within the DFG SPP 1158 “Antarctic Research” (joint project with Thomas Laepple, Alfred Wegener Institut, Potsdam)
• DFG project “Multi-fidelity, active learning strategies for exciton transfer in cryptophyte antenna complexes” (duration 2026-2029)
  Research project within the second phase of the DFG SPP 2363 “Utilization and Development of Machine Learning for Molecular Applications – Molecular Machine Learning” (joint project with Ulrich Kleinekathöfer, Physics, Constructor University Bremen)
• DFG subproject “Data-driven surrogate modelling for differential-algebraic port-Hamiltonian systems” (C03) (duration: 2025-2028)
  Subproject of the CRC 1701 “Port-Hamiltonian Systems” (co-PI together with Michael Günther)
• DFG subproject “Benchmark platform for port-Hamiltonian systems” (S) (duration: 2025-2028)
  Subproject of the CRC 1701 “Port-Hamiltonian Systems” (co-PI together with Hanno Gottschalk)

Finished projects

• MarDATA project “Digital Ice Cores: Paleo-Climate reconstruction using Bayesian methods” (duration: 2023-2026)
  Helmholtz School for Marine Data Science (joint project with Thomas Laepple, Alfred Wegener Institute & U. Bremen)
• DFG project “Multi-fidelity, Active Learning Strategies for Exciton Transfer Among Adsorbed Molecules” (duration 2022-2026)
  Research project within the first phase of the DFG SPP 2363 “Utilization and Development of Machine Learning for Molecular Applications – Molecular Machine Learning” (joint project with Ulrich Kleinekathöfer, Physics, Jacobs University Bremen)
• MarDATA project “Bayesian Chronology Modelling for Paleoclimate Archives” (duration: 2022-2026)
  Helmholtz School for Marine Data Science (joint project with Florian Adolphi, Alfred Wegener Institute)
• DFG project “Excitation Energy Transfer in a Photosynthetic System with more than 100 Million Atoms” (duration: 2021-2025)
  Individual Research Grant funded by DFG (joint project with Ulrich Kleinekathöfer, Physics, Constructor University Bremen)

Software

Find our recent software contributions for publications and beyond on our Github site https://github.com/SM4DA.

In addition, our software developments include:

• hmglib – Open Source library for hierarchical matrices on GPU (https://github.com/zaspel/hmglib)
• MPLA – Open Source multi-GPU parallel library for dense iterative solvers (https://github.com/zaspel/MPLA)
• QML – Extension of the Open Source Quantum Machine Learning library by multi-fidelity techniques (for now hosted in the fork https://github.com/zaspel/qml)
• UQ on GPU – (Multi-) GPU parallel kernel-based methods for uncertainty quantification in random partial differential equations
• AMG on GPU – Hybrid GPU-based Ruge-Stüben algebraic multigrid
• NaSt3DGPF – Multi-GPU MPI-parallel version of the fluid mechanics solver NaSt3DGPF (https://ins.uni-bonn.de/media/public/u/griebel/NaSt3DGPF/projects.html)