Barbara Solenthaler is a senior research scientist at the Computer Graphics Laboratory at ETH Zurich, Switzerland, where she is heading the simulation and animation group. She received her Ph.D. in Computer Science from the University of Zurich. She is also affiliated with the Institute for Advanced Study at the Technical University of Munich, where she holds a Hans Fischer Fellowship. Her research focuses on physics simulations and animations for computer graphics applications, including visual effects, games, interactive design processes, virtual reality and biomedical computing. She is particularly interested in methods for efficient, robust and artist-controllable simulations, and uses deep learning for physics simulations to transform and simplify existing workflows and computations. She regularly serves on technical program committees of major graphics conferences including ACM SIGGRAPH, Eurographics and ACM SIGGRAPH / Eurographics Symposium on Computer Animation. She was a conference chair of the ACM SIGGRAPH / Eurographics Symposium on Computer Animation in 2016 and poster chair of Eurographics 2015. She has received multiple Swiss research grants, holds multiple US patents, and has co-founded the company Apagom AG that provides a real-time fluid engine using machine learning technologies. She was recently elected as a member of the GI focus group animation and simulation.
Selected Awards
2019, Hans Fischer Fellowship at the Institute for Advanced Study, Technical University of Munich
2017, Best Paper Awards of Educational Data Mining
2016, ACM Recognition of Service Award
2014-2019, Recipient of SNSF, ETH and Innosuisse research grants
2011, Best Paper Awards Virtual Reality Interaction and Physical Simulation
2010, Nominated for the GI Dissertation Award
2009, Fritz-Kutter Dissertation Award
Research Interests
Physics-based modeling and simulation, data-driven simulations, deep learning for physics, real-time computations and technologies, artist-controllable simulations
Selected Publications
E. Franz, B. Solenthaler, N. Thürey. Global Transport for Fluid Reconstruction with Learned Self-Supervision. CVPR (oral), 2021.
L. Schweri, S. Foucher, J. Tang, V. Azevedo, T. Günther, B. Solenthaler. A Physics-Aware Neural Network Approach for Flow Data Reconstruction from Satellite Observations. Front. Clim. 3:656505, 2021.
J. Tang, G. Cordonnier, V. Azevedo, M. Gross, B. Solenthaler. Reduced Domain Decomposition for Efficient Optimization of Fluids. Computer Graphics Forum (Eurographics) 2021.
S. Wiewel, B. Kim, V. Azevedo, B. Solenthaler, N. Thuerey. Latent Space Subdivision: Stable and Controllable Time Predictions for Fluid Flow. Symposium on Computer Animation, 2020.
Y.L. Chen, J. Meier, B. Solenthaler, V. C. Azevedo. An Extended Cut-Cell Method for Sub-Grid Liquids Tracking with Surface Tension. ACM Transactions on Graphics (SIGGRAPH Asia), 2020.
B. Kim, V. C. Azevedo, M. Gross, B. Solenthaler. Lagrangian Neural Style Transfer for Fluids. ACM Transactions on Graphics (SIGGRAPH), 2020.
S. Wiewel, B. Kim, V. Azevedo, B. Solenthaler, N. Thuerey. Latent Space Subdivision: Stable and Controllable Time Predictions for Fluid Flow. Symposium on Computer Animation, 2020.
R. Wampfler, S. Klingler, B. Solenthaler, V. Schinazi, M. Gross. Affective State Prediction Based on Semi-Supervised Learning from Smartphone Touch Data. ACM CHI 2020.
S. Liu, M. Srinivasan, R.Mörzinger, M. Lancelle, T. Beeler, M. Gross, B. Solenthaler, V. Fehmer, I. Sailer. Reliability of a Three-dimensional Facial Camera for Dental and Medical Applications: A Pilot Study. Journal of Prosthetic Dentistry, 2019.
B. Kim, V. C. Azevedo, M. Gross, B. Solenthaler. Transport-Based Neural Style Transfer for Smoke Simulations. ACM Transactions on Graphics (Proceedings SIGGRAPH Asia), 2019.
B. Kim, V. Azevedo, N. Thürey, T. Kim, Markus Gross, B. Solenthaler. Deep Fluids: A Generative Network for Parameterized Fluid Simulations. Computer Graphics Forum (Proceedings of Eurographics), 2019.
D. Koschier, J. Bender, B. Solenthaler, M. Teschner. Smoothed Particle Hydrodynamics for Physically-Based Simulation of Fluids and Solids. In Tutorial Proceedings of Eurographics, 2019.
M. Ihmsen, J. Orthmann, B. Solenthaler, A. Kolb, M. Teschner. SPH Fluids in Computer Graphics. STAR - State of The Art Report, Eurographics, 2014.
M. Ihmsen, J. Cornelis, B. Solenthaler, C. Horvath and M. Teschner. Implicit Incompressible SPH. IEEE Transactions on Visualization and Computer Graphics, 20(3), 2014.
C. Horvath and B. Solenthaler. Mass Preserving Multi-Scale SPH. Pixar Technical Memo #13-04, 2013.
N. Akinci, M. Ihmsen, G. Akinci, B. Solenthaler and M. Teschner. Versatile Rigid-Fluid Coupling for Incompressible SPH. ACM Transactions on Graphics (Proceedings of SIGGRAPH), 31(4), 2012.
B. Solenthaler and M. Gross. Two-Scale Particle Simulation. ACM Transactions on Graphics (Proceedings of SIGGRAPH), 30(4), 2011.
B. Solenthaler and R. Pajarola. Predictive-Corrective Incompressible SPH. ACM Transactions on Graphics (Proceedings of SIGGRAPH), 28(3), 2009.
Franz, Erik; Solenthaler, Barbara; Thuerey, Nils: Learning to Estimate Single-View Volumetric Flow Motions without 3D Supervision. , 2023 mehr…BibTeX
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2021
Franz, Erik; Solenthaler, Barbara; Thuerey, Nils: Global Transport for Fluid Reconstruction with Learned Self-Supervision. 2021 mehr…BibTeX
2020
Wiewel, S.; Kim, B.; Azevedo, V. C.; Solenthaler, B.; Thuerey, N.: Latent Space Subdivision: Stable and Controllable Time Predictions for Fluid Flow. Computer Graphics Forum 39 (8), 2020, 15-25 mehr…BibTeX
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2019
Kim, Byungsoo; Azevedo, Vinicius C.; Thuerey, Nils; Kim, Theodore; Gross, Markus; Solenthaler, Barbara: Deep Fluids: A Generative Network for Parameterized Fluid Simulations. Computer Graphics Forum 38 (2), 2019, 59-70 mehr…BibTeX
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