- Affiliation: Carnegie Mellon University
- Web Site: https://www.cs.cmu.edu/~kmcrane/
- Email: kmcrane [at] cs.cmu.edu
- Title: Monte Carlo Geometry Processing
- Date & room: Thursday, 6th July at 14:00 - 15:00 (Rooms: 1A+1B)
Systems throughout nature exhibit vast geometric and material complexity, making them impossible to simulate with traditional mesh-based methods. A common approach is to simplify the original model (e.g., via coarsening or homogenization), yet subtle differences in fine-scale geometry can have a major impact on large-scale behavior. In contrast, Monte Carlo rendering provides beautiful and predictive simulation of light transport even on imperfect meshes with almost unlimited detail. This talk explores how the benefits of Monte Carlo rendering can be extended to a much broader class of partial differential equations (PDEs) appearing in science and engineering, via several recent extensions of the little-known "walk on spheres (WoS)" method.
Keenan Crane is the Michael B. Donohue Associate Professor of Computer Science and Robotics at Carnegie Mellon University, and a member of the Center for Nonlinear Analysis. He is a Packard Fellow and recipient of the NSF CAREER Award, was a Google PhD Fellow in the Department of Computing and Mathematical Sciences at Caltech, and was an NSF Mathematical Postdoctoral Research Fellow (MSPRF) at Columbia University. Dr. Crane's work applies insights from differential geometry to build fundamental representations and algorithms for processing, designing, and analyzing geometric data. This work has been featured in venues such as Notices of the AMS and Communications of the ACM, as well as in the popular press through outlets such as WIRED, Popular Mechanics, National Public Radio, The New York Times, and Scientific American.