Deep Learning for Fluid Simulations
Event date:  February 5, 2018 4:00 PM  to 5:00 PM

Talk Abstract

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 discuss using deep learning for physics problems, and outline research directions to alleviate the inherent difficulties of fluids simulations with the help of deep convolutional neural networks. As powerful tools to approximate complex nonlinear functions these networks can enable new directions of working with fluid simulations. I will show several recent examples of how fluid simulations and neural networks can work together, e.g., to synthesize new simulations with pre-computed patches of flow data, or to enable interactive liquids applications by warping space-time surfaces. 

In the end, I will also discuss possible future directions for this area. It's of course hard to predict how well deep learning will do in the long run, but fluids (as placeholders for complex physics phenomena in general) are posing very interesting research challenges for deep learning techniques.

Speaker’s Bio

Nils Thuerey is an Assistant-Professor at the Technical University of Munich (TUM). He works in the field of computer graphics, with a particular emphasis on physically-based animation. One focus area of his research targets the simulation of fluid phenomena, such as 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.

After studying computer science, Nils 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. He received a tech-Oscar from the AMPAS in 2013 for his research on controllable smoke effects. Subsequently, he worked for three years as R&D lead at ScanlineVFX, before he started at TUM in October 2013.

More information on 


University of Stuttgart, VISUS-Building, Allmandring 19, Vaihingen
Powerwall Room -01.116

University of Konstanz, Universitätsstr. 10, Konstanz
Powerwall C202 (Live Transmission)