Sebastian Wohner

Sebastian Wohner is a researcher at the Chair of Computer Graphics and Visualization (Prof. Westermann) at the Technical University of Munich. His work focuses on advanced visualization techniques, machine learning applications in graphics, and GPU-accelerated algorithms for 3D design and simulation. He actively contributes to projects such as the NVIDIA CUDA Research Center and ERC-funded initiatives like SaferVis and realFlow, emphasizing real-time liquids and safer visualization systems.

His research interests span 3D Gaussian splatting, topology optimization, neural fields for statistical dependencies, and spatio-temporal flow visualization. He has pioneered methods for compressing meteorological ensembles and accelerating novel view synthesis in consumer devices. Wohner also explores GPU-based linear algebra optimizations and efficient rendering techniques for ribbons and twisted lines.

In teaching, he leads courses on game physics, visual data analytics, deep learning in computer graphics, and topology optimization. Notable contributions include the development of the Particle Engine and Bunny Demo applications, as well as advancements in differentiable rendering and robotic perception systems. His work bridges theoretical foundations with practical implementations in both academia and industry.