I'm a Senior Research Scientist in the High Fidelity Physics research group at NVIDIA. Before joing NVIDIA, I did my PhD in Computer Science at Carnegie Mellon University, advised by Keenan Crane. I'm broadly interested in developing new algorithms at the intersection of geometry processing, simulation and rendering. My 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.

I received an Nvidia Graduate Fellowship, a Carnegie Mellon Graduate Presidential Fellowship, and an Honorably Mention Best Paper Award at SIGGRAPH for my work on Monte Carlo PDE solvers. I've also received the Symposium on Geometry Processing best software aware for the Boundary First Flattening application to quickly and robustly generate UV maps. Previously, I worked at IrisVR, Inc. as a core graphics engineer and received my Bachelor’s in Physics and Computer Science from Columbia University. Find my CV here.

Recent Work

Decorrelating ReSTIR Samplers via MCMC Mutations

Sawhney, Lin, Kettunen, Bitterli, Ramamoorthi, Wyman, Pharr

ACM Transactions on Graphics (2023)

Paper  |  Supplemental  |  Video

Walk on Stars: Grid-Free Monte Carlo for Neumann Boundary Conditions

Sawhney*, Miller*, Gkioulekas, Crane

ACM Transactions on Graphics (2023)

Paper  |  Code  |  Tutorial  |  Talk

Boundary Value Caching for Walk on Spheres

Miller*, Sawhney*, Crane, Gkioulekas

ACM Transactions on Graphics (2023)

Paper  |  Code  |  Talk

Grid-Free Monte Carlo for PDEs with Spatially Varying Coefficients

Sawhney*, Seyb*, Jarosz, Crane

ACM Transactions on Graphics (2022)

Best Paper (Honorable Mention)

Paper  |  Supplemental  |  Code  |  Talk

Monte Carlo Geometry Processing

Sawhney, Crane

ACM Transactions on Graphics (2020)

Paper  |  Project Page  |  Talk

Boundary First Flattening

Sawhney, Crane

ACM Transactions on Graphics (2018)

SGP Best Software Award (2019)

Paper  |  Project Page  |  Talk  |  Web Demo


Header only C++ library for fast vectorized closest point queries

Project Page


Fast & flexible framework for 3D geometry processing on the web

Project Page


Sparse & dense matrix routines with Cholesky, LU & QR support on the web

Project Page


Multi Agent Reinforcement Learning

Deep Reinforcement Learning agents playing tag

Report  |  Code

Medial Axis Transform

Undergrad. research project on computing medial axis

Report  |  Code