The temporal evolution of physically based fluid simulations is my current research topic. I apply machine learning techniques on simulated fluid data and predict the temporal behavior of the physical quantities like pressure or velocity fields.
Since 2018 I’m a Ph.D. candidate in Nils Thuerey’s group.
Besides organizing the Computer Games Laboratory Course I am also supervising Bachelor’s or Master’s Theses. See below for a list of the most recent supervised theses.
E-mail: wiewel (at) in.tum (dot) de
- Steffen Wiewel, Moritz Becher and Nils Thuerey, “Latent-space Physics: Towards Learning the Temporal Evolution of Fluid Flow”, Eurographics 2019, last update March 2019 [Project]
- Steffen Wiewel, “Advanced Sequence Learning for Liquid Simulations”, M.Sc. Thesis, TUM, March 2018. (English)
- Steffen Wiewel, “Practical Applications of the DirectX 11 Depth-Buffer”, B.Sc. Thesis, TUM, September 2015. (German)
- Latent-space Physics: Towards Learning the Temporal Evolution of Fluid Flow, Eurographics Conference 2019, May 2019
- Summer 2019: Grundlagen Algorithmen und Datenstrukturen
- Summer 2019: Computer Games Laboratory
- Summer 2018: Computer Games Laboratory
- Moritz Becher, “Transfer Learning for Fluid Simulation”, M.Sc. Thesis, TUM, February 2019. (English)
- Tobias Zengerle, “Physics-based Sequence to Sequence
Networks with Convolutions”, B.Sc. Thesis, TUM, August 2018. (English)