Department of Computer Science
Computer Graphics Laboratory
ETH Zurich
Universitätsstrasse 6
CNB G 106.1
Barbara Solenthaler is a senior research scientist at the Computer Science department at ETH Zurich, where she leads the research on simulation and animation at the Computer Graphics Laboratory. Prior to joining ETH, she received her Ph.D. in Computer Science from the University of Zurich. In her research she develops algorithms and techniques for data-driven physics simulations, where a particular challenge is to synergistically combine machine learning with 3D modeling and the laws of dynamics. Her research includes the simulation of digital humans, image based modeling, and artist-controllable fluid simulations, aiming at transforming and simplifying workflows in visual effects and medical fields. Barbara is currently also affiliated with the Institute for Advanced Study at the Technical University of Munich, where she holds a Hans Fischer Fellowship awarded by the Siemens AG on digital twin technologies. Barbara serves on various technical program and organization committees of major graphics conferences (e.g., SIGGRAPH and EG IPC, SCA 2016 chair, SCA 2022 awards chair), is appointed as an Associate Editor of Computer Graphics Forum, and is a co-founder of Apagom AG that provides a real-time fluid engine using machine learning.
Our work on animating digital humans received the SIGGRAPH 2022 Honorable Mentions Award.
Digital humans for orthodontics and digital dentistry: our project with Align Technology will be presented at the ETH Industry Days 2022.
Our research on 3D modeling and treatment planning for cleft lip and palate was presented at Science City 2021.
Our volume stylization with neural networks was used in Hollywood.
The Eurographics 2021 Günther Enderle Best Paper Award was awarded to our work on art-directable fluids.
Our current research focuses on deep learning based physics simulations, art-directable simulations, physics-based digital humans, digital humans for medical applications, and character animation.
I teach the course units Parallel Programming, Seminar on Digital Humans, and Doctoral Seminar in Visual Computing. Past courses include Physically-based Simulation in Computer Graphics and Engineering Tool: Case Study Physics Simulations.
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Differentiable Simulation for Outcome-driven Orthognathic Surgery Planning
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Implicit Neural Representation for Physics-driven Actuated Soft Bodies
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Neural Green’s Function for Laplacian Systems
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A Survey on SPH Methods in Computer Graphics
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Deep Reconstruction of 3D Smoke Densities from Artist Sketches
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Affective State Prediction from Smartphone Touch and Sensor Data in the Wild
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SPH Crowds: Agent-based Crowd Simulation up to Extreme Densities Using Fluid Dynamics
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Global Transport for Fluid Reconstruction with Learned Self-Supervision
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A Physics-Aware Neural Network Approach for Flow Data Reconstruction from Satellite Observations
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Honey I Shrunk the Domain: Reduced Domain Decomposition for Efficient Optimization of Fluids
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Extreme-Density Crowd Simulation: Combining Agents with Smoothed Particle Hydrodynamics
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An Extended Cut-Cell Method for Sub-Grid Liquids Tracking with Surface Tension
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Latent Space Subdivision: Stable and Controllable Time Predictions for Fluid Flow
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Lagrangian Neural Style Transfer for Fluids
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Image Reconstruction of Tablet Front Camera Recordings in Educational Settings
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Glyph-Based Visualization of Affective States
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Frequency-Aware Reconstruction of Fluid Simulations with Generative Networks
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Neural Smoke Stylization with Color Transfer
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Affective State Prediction Based on Semi-Supervised Learning from Smartphone Touch Data
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Transport-Based Neural Style Transfer for Smoke Simulations
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Affective State Prediction in a Mobile Setting using Wearable Biometric Sensors and Stylus
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Smoothed Particle Hydrodynamics for Physically-Based Simulation of Fluids and Solids
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Reliability of a Three-dimensional Facial Camera for Dental and
Medical Applications: A Pilot Study
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Deep Fluids: A Generative Network for Parameterized Fluid Simulations
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Ten Years of Research on Intelligent Educational Games for Learning Spelling and Mathematics
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Efficient Feature Embeddings for Student Classification with Variational Auto-encoders
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Anaglyph Caustics with Motion Parallax
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Temporally Coherent Clustering of Student Data
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Stealth Assessment in ITS - A Study for Developmental Dyscalculia
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Data-driven Fluid Simulation using Regression Forests
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HeapCraft: Interactive Data Exploration and Visualization Tools for Understanding and Influencing Player Behavior in Minecraft
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Quantifying and Predicting Collaboration in Shared Virtual Worlds
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Example-based Structure Synthesis
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HeapCraft Social Tools: Understanding and Improving Player Collaboration in Minecraft
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Statistical Analysis of Player Behavior in Minecraft
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On the Performance Characteristics of Latent-Factor and Knowledge Tracing Models
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A Parallel Architecture for IISPH Fluids
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SPH Fluids in Computer Graphics
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Mass Preserving Multi-Scale SPH
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Modelling and Optimizing Mathematics Learning in Children
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Implicit Incompressible SPH
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Cluster-Based Prediction of Mathematical Learning Patterns
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Towards a Framework for Modelling Engagement Dynamics in Multiple Learning Domains
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Versatile Rigid-Fluid Coupling for Incompressible SPH
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Two-Scale Particle Simulation
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SPH Based Shallow Water Simulation
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Interactive SPH Simulation and Rendering on the GPU
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Inkompressible Fluid Simulation und verbesserte Oberflächenbehandlung mit SPH
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Incompressible Fluid Simulation and Advanced Surface Handling with SPH
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Performance Comparison of Parallel PCISPH and WCSPH
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Predictive-Corrective Incompressible SPH
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Density Contrast SPH Interfaces
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Adaptive Sampling and Rendering of Fluids on the GPU
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A Unifed Particle Model for Fuid-Solid Interactions
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Efficient Refinement of Dynamic Point Data
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Particle-Based Fluid-Fluid Interaction
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Simultaneous Topology and Stiffness Identification for Mass-Spring Models based on FEM Reference Deformations
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