Nils Thuerey
Data-driven Fluid Simulations with Neural Networks
Physics simulations for virtual smoke, explosions or water are by now crucial tools for special effects. Despite their widespread use, it is still difficult to get get these simulations under control, and they are still far too expensive for practical interactive applications. In this talk I will outline research directions to alleviate these inherent difficulties with machine learning techniques based on neural networks. These networks can learn and represent highly nonlinear functions, which turns out to be highly useful in the flow simulation context. I will show several examples of how fluid simulations and neural networks can work together, and then give an outlook for this direction of research. Predictions are of course difficult, even more so if they concern the future, but I believe there are many exciting venues for fluid simulations and neural networks.
Nils Thuerey works on physically-based animations, with a particular emphasis on fluids effects, i.e., water and smoke. These simulations find applications as visual effects in computer generated movies and digital games. 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. Currently, Nils is an Assistant-Professor at the Technical University of Munich. Previously, he worked as R&D lead at ScanlineVFX, and as a post-doctoral researcher at ETH Zurich. In 2013, he received a tech-Oscar from the AMPAS for his work on the Wavelet Turbulence algorithm.