Prerequistes: 18.02, 18.06; 6.837 or 6.869 recommended
Instructor: Professor Justin Solomon (email@example.com)
Schedule: TR1-2:30 in 32-124
Introduces mathematical, algorithmic, and statistical tools needed to analyze geometric data, with applications to computer graphics, computer vision, medical imaging, machine learning, architecture, and other fields. Potential topics include: applied introduction to differential geometry; discrete notions of curvature; PDE on geometric domains via the finite element method (FEM) and discrete exterior calculus (DEC); computational spectral geometry; correspondence and mapping; metric geometry; level set methods; descriptors; shape collections; and vector field design.