[Colloquium] Convex Relaxation Strategies for Geometry Processing

[Jose J Fragoso via Colloquium]

UNIVERSITY OF CHICAGO
COMPUTER SCIENCE DEPARTMENT
PRESENTS


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Justin Solomon
Massachusetts Institute of Technology (MIT)
Associate Professor



Tuesday, October 15th
12:00pm – 1:00pm
In Person: John Crerar Library Rm 390

Title: Convex Relaxation Strategies for Geometry Processing

Abstract: While classical models in geometry processing often boil down to linear systems of equations, modern techniques depend on solution of nonlinear and possibly nonconvex problems. In this talk, I will share a variety of works that show how convex relaxations can be used to extract solutions to difficult geometry processing problems, often with theoretical guarantees of optimality. Our methods are applicable to a wide range of geometry processing tasks, from solution of partial differential equations to design of frame fields and optimization of minimal surfaces. This talk will cover collaborative research with Mirela Ben-Chen, Albert Chern, Michal Edelstein, Nestor Guillen, Zoë Marschner, Leticia Mattos Da Silva, David Palmer, Dmitriy Smirnov, Oded Stein, Stephanie Wang, Paul Zhang, and others.


Bio:  Justin Solomon is an associate professor in MIT's Department of Electrical Engineering and Computer Science.  He directs the Geometric Data Processing group in the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL), which studies problems at the intersection of geometry, large-scale optimization, and applications in graphics and machine learning.  Prof. Solomon is visiting the University of Chicago on October 7-18.




Host: Rana Hanocka



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