Jonas Zehnder

Papers

Total Citations

158

H-Index

About

Jonas Zehnder is a computational researcher specializing in physics-based simulation, differentiable dynamics, and multi-body systems — fields at the intersection of computer graphics, robotics, and machine learning. His most recognized contribution is the development of ADD (Analytically Differentiable Dynamics), a novel differentiable dynamics solver capable of handling frictional contact for both rigid and deformable objects within a unified framework. By introducing a principled mollification of normal and tangential contact forces, Zehnder's approach elegantly circumvents the fundamental challenges posed by the non-smooth nature of contact dynamics — a long-standing bottleneck in simulation-based optimization and learned control. This work has accumulated over 140 citations, reflecting its significant uptake across the graphics and robotics communities where differentiable simulation is increasingly central to data-driven and optimization-based pipelines. His research addresses a critical need: enabling gradient-based optimization through physically realistic contact interactions, which has broad implications for trajectory optimization, character animation, and soft robotics. Zehnder's contributions represent an important step toward making complex physical simulations fully compatible with modern differentiable programming paradigms.