Prof. Dr. Nils Thuerey
Academic Career and Research Areas
Professor Thuerey (b. 1979) works in the field of computer graphics, with a particular emphasis on physics-based deep learning algorithm. One focus of his research targets the simulation of fluid phenomena, such as water and smoke. These simulations find applications as visual effects in computer generated worlds, but also in many fields of engineering. Examples of his work are novel algorithms to make simulations easier to control, to handle detailed surface tension effects, and to increase the amount of turbulent detail.
After studying computer science, Professor Thuerey acquired a PhD for his work on liquid simulations in 2006. He received both degrees from the University of Erlangen-Nuremberg. Until 2010 he held a position as a post-doctoral researcher at ETH Zurich, in collaboration with Ageia/Nvidia. Subsequently, he worked for three years as Research & Development Lead at ScanlineVFX, developing large scale physics-simulators for visual effects. Since fall 2013 he has been Professor for Physics-based Simulation at TUM.
Awards
- Starting Grant "realFlow", European Research Council (ERC) (2014)
- Technical Oscar (Technical achievement award of the AMPAS) (2012)
- University of Erlangen Staedtler Graduation Award (2008)
Key Publications (all publications)
Lino M., Pfaff T., Thuerey N.: "Learning Distributions of Complex Fluid Simulations with Diffusion Graph Networks". International Conference on Learning Representations (ICLR). 2025.
AbstractHolzschuh B., Vegetti S., Thuerey N.: "Solving Inverse Physics Problems with Score Matching". Advances in Neural Information Processing Systems (NeurIPS). 2024.
AbstractList B., Chen L., Thuerey N.: "Learned Turbulence Modelling with Differentiable Fluid Solvers". Journal of Fluid Mechanics (JFM). 2022.
AbstractUm K., Fei Y., Brand R., Holl P., Thuerey N.: "Solver-in-the-Loop: Learning from Differentiable Physics to Interact with Iterative PDE-Solvers". Advances in Neural Information Processing Systems (NeurIPS). 2020.
AbstractThuerey N., Weissenow K., Prantl L., Hu X.: "Deep Learning Methods for Reynolds-Averaged Navier-Stokes Simulations of Airfoil Flows". Journal of the American Institute of Aeronautics and Astronautics (AIAA). 2020.
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