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Prof. Dr. Peter Zaspel
Prof. Dr.
Professor of Computer Science
Computer Science & Electrical Engineering

 

Jacobs University Bremen gGmbH
Campus Ring 1 | 28759 Bremen | Germany

Email: 
p.zaspel [at] jacobs-university.de
Office: 
Research I, Room 168
Research Interests: 
  • Analysis and prediction techniques for data and simulation
    • machine learning (e.g. by kernel ridge regression)
    • inference / data assimilation and uncertainty quantification
    • multi-fidelity techniques / sparse grid (combination technique)
    • approximation in reproducing kernel Hilbert spaces
    • low-rank approximation (e.g. hierarchical matrices)
  • Parallel and scalable algorithms
    • optimal complexity algorithms
    • algorithmics for many-core processors / GPUs
    • High Peformance Computing
    • development of scientific software
  • Interdisciplinary applications
    • quantum chemistry
    • medical imaging
    • two-phase flows
    • plasma physics
Publications: 
  • M. Griebel, Ch. Rieger, P. Zaspel. Kernel-based stochastic collocation for the random two-phase Navier-Stokes equations. Accepted for publication in International Journal for Uncertainty Quantification, April 2019.
  • P. Zaspel. Ensemble Kalman filters for reliability estimation in perfusion inference. International Journal for Uncertainty Quantification, 9(1):15-32, 2019.
  • P. Zaspel, B. Huang, H. Harbrecht, O. A. von Lilienfeld. Boosting quantum machine learning models with multi-level combination technique: Pople diagrams revisited. Journal of Chemical Theory and Computation, 15(3):1546-1559, 2019.
  • H. Harbrecht, P. Zaspel. On the algebraic construction of sparse multilevel approximations of elliptic tensor product problems. Journal of Scientific Computing, Springer, 78(2):1272-1290, 2019.
  • P. Zaspel. Algorithmic patterns for H matrices on many-core processors. Journal of Scientific Computing, Springer, 78(2):1174-1206, 2019.
  • P. Zaspel. Subspace correction methods in algebraic multi-level frames. Linear Algebra and its Applications, Vol. 488(1), Jan. 2016, pp. 505-521.
  • D. Pflüger, H.-J. Bungartz, M. Griebel, F. Jenko, T. Dannert, M. Heene, A. Parra Hinojosa, C. Kowitz and P. Zaspel: EXAHD: An Exa-scalable Two-Level Sparse Grid Approach for Higher-Dimensional Problems in Plasma Physics and Beyond. In: Lopes L. et al. (eds) Euro-Par 2014: Parallel Processing Workshops. Euro-Par 2014. Lecture Notes in Computer Science, vol 8806. Springer, Cham, 2014.
  • P. Zaspel and M. Griebel. Solving incompressible two-phase flows on multi-GPU clusters. Computer & Fluids, 80(0):356 - 364, 2013.
  • P. Zaspel and M. Griebel. Massively parallel fluid simulations on Amazon's HPC cloud. In Network Cloud Computing and Applications (NCCA), 2011 First International Symposium on, pages 73 -78, Nov. 2011.
  • P. Zaspel and M. Griebel. Photorealistic visualization and fluid animation: coupling of Maya with a two-phase Navier-Stokes fluid solver. Computing and Visualization in Science, 14(8):371-383, 2011.
  • M. Griebel and P. Zaspel. A multi-GPU accelerated solver for the three-dimensional two-phase incompressible Navier-Stokes equations. Computer Science - Research and Development, 25(1-2):65-73, May 2010.