Rohan Sawhney joined the High-Fidelity Physics research group as a researcher in 2023. Before joining NVIDIA, he did his PhD in Computer Science at Carnegie Mellon University, advised by Keenan Crane. Rohan is broadly interested in developing new algorithms at the intersection of geometry processing, simulation and rendering. His current research explores how core problems in PDE-based geometric computing can be efficiently and reliably solved via grid-free Monte Carlo methods without any volumetric mesh generation, taking inspiration from algorithms for photorealistic rendering.

Rohan received an Nvidia Graduate Fellowship and an Honorable Mention Best Paper Award at SIGGRAPH for his work on Monte Carlo PDE solvers. He has also received the Symposium on Geometry Processing best software award for the Boundary First Flattening application to quickly and robustly generate UV maps.