Allan P. Engsig-Karup
Associate Professor in Scientific Computing, M.Sc.(Eng.), Ph.D.
Faculty Member of Center For Energy Resources Engineering (CERE), DTU
Faculty Member of The Danish Center for Applied Mathematics and Mechanics (DCAMM)

	  P. Engsig-Karup Scientific Computing
DTU Compute, Technical University of Denmark
Matematiktorvet, Building 303b/108
2800 Kgs.-Lyngby
Tel: (+45) 45 25 30 73
Fax: (+45) 45 88 26 73
Skype: a.p.engsigkarup
apek @

Research interests linked to applications of basic and applied mathematics research for Advanced Simulations and innovative use of Modern Computing Technologies and contribute to sustainability objectives

Publications, presentations, etc. or check out my profile at ResearchGate.

Internships with companies and research institutions

University Teaching

Course catalogue at DTU: Catalogue

Organized PhD schools, Workshops and Seminars

  • 2009, DGFEM2009 with Prof. Jan S. Hesthaven.
  • 2010, GPU2010 with Prof. Hendrik Lensch, Robert Strodzka and Timothy Lanfear.
  • 2011, GPU2011with Assoc. Prof. Tim Warburton.
  • 2011, ITSOL2011 with Prof. C. T. Kelley.
  • 2011, Workshop on GPU Programming in Python with PostDoc Andreas Klockner.
  • 2012, DGFEM2012 with Prof. Jan S. Hesthaven.
  • 2013, Seminar on Modern Scientific Computing Trends with Assoc. Prof. Luke Olson and Prof. Xing Cai.
  • 2014, ITSOL2014 with Prof. C. T. Kelley.
  • 2015, Seminar on Modern Scientific Computing Trends with Directeur de Recherche CNRS Olivier Le Maitre
  • 2015-2016 Inspirational seminar series on PDE-constrained optimization
    • October, Prof. Anton Evgrafov
    • November, Prof. Bijan Mohammedi.
    • December, Prof. Roland Herzog.
    • January, Prof. Michael Pedersen.
  • 2016, Workshop on How To Scale Scientific Applications from Laptops to Supercomputers with PETSc with Karl Rupp.
  • 2018, Numerical Methods for Uncertainty Quantification UQ2018 with Directeur de Recherche CNRS Olivier Le Maitre.
  • 2020, Model Order Reduction Summer School (MORSS) 2020 organized by EPFL (Ecole polytechnique federale Lausanne), DTU - Technical University of Denmark, a Eindhoven University of Technology (EuroTech Universities Alliance)
  • 2022, PhD school on Scientific Machine Learning with Dr. Christopher Rackauckas, MIT, US.
  • 2022-2023 Inspirational seminar series on Mathematics of Data Science
  • At the Scientific Computing Section of DTU Compute, we also host Scientific Computing Seminars.

    Research and Innovation projects

    Active and recent research areas in new technologies, computational mathematics and their applications

    All highlights are build from scratch with an aim to deliver state-of-the-art approaches using advanced numerical methods as a part of research effort in my group.

    Research in paradigm shifts in scientific computing using modern parallel programming paradigms and emerging many-core and heterogeneous architectures ranging from work desktops to the largest super-computing clusters in the world.
    Novel algorithms and high-performance computing for fast (possibly real-time) calculations to pave the way for novel marine and naval hydrodynamics calculations.
    Novel and efficient spectral (high-order) and adaptive algorithms for uncertainty quantification of problems with high dimensionality, data science, machine learning and stochastic simulations.
    Massively parallel and scalable algorithms such as multigrid and multi-level algorithms for scientific engineering applications, e.g. reservoir simulation and hydrodynamics.

    Novel application proof-of-concepts for engineering analysis, e.g. offshore engineering, computational fluid dynamics, room acoustics and vibro-acoustics.

    Research in efficient and robust high-order unstructured numerical methods and time-dependent models.

    Scientific Software Engineering

    Drivers of the research are scientific software for scientific investigation.

    Poster highlights of research

    Supervision in Research projects (selected and recent)

    Community service

    2010, Co-founder (with colleagues at Scientific Computing Section) of GPULAB with strong focus on Scientific GPU Computing, fundamental aspects of high-performance and heterogenous computing on modern many-core architectures and software development for proofs of concepts related to next-generation scientific applications using modern programming paradigms (CUDA/OpenCL) and tools. GPUlab was designated Nvidia CUDA Teaching Center May 2012 and Nvidia CUDA Research Center (PI: Allan P. Engsig-Karup) since November 2012.

    I am a member of the Scientific Council of Danish Center for Applied Mathematics and Mechanics (DCAMM).