Geometry Processing and Fabrication

University of Toronto

Current geometric design tools are indirect and require esoteric training. Ad hoc pipelines for preparing geometry for fabrication involve many phases and typically many different people or groups. Meanwhile, core geometry processing algorithms are not robust to data imperfections, which are now commonplace. Our approach is fundamentally different. We adapt fundamental mathematics to work with messy geometric data. An archetypical example is our past work on generalizing the classic formula for determining the inside from the outside of a curve to messy representations of 3D surface geometry commonly found throughout computer graphics and computer aided design. This work enables downstream processing such as physical simulation and fabrication.

 

We are pioneering large-scale testing of geometric algorithms. This empirical evidence of robust implementation complements correctness proofs. Robust core subroutines allows us to create complete geometric design systems connecting creation to fabrication in a single pipeline, similar to “what you see is what you get” word processing.

Lab Leader

Alec Jacobson

Canada Research Chair

Assistant Professor

Faculty of Arts and Science
Department of Computer Science 

University of Toronto

Industry Partners

Autodesk logo

Lab Team

Eitan Grinspun
Columbia University

David I.W. Levin

University of Toronto 

Maks Ovsjanikov

Ecole Polytechnique

Leonardo Sacht

Universidade Federal de Santa Catarina

Postdocs and Graduate Trainees

Seungbae Bang

Postdoctoral Fellow, University of Toronto

Thomas Davies

MSc Candidate, University of Toronto

Josh Holinaty

MSc Candidate, University of Toronto

Hsueh-Ti Derek Liu

PhD Candidate, University of Toronto

Sarah Kushner

PhD Candidate, University of Toronto

Silvia Sellán

PhD Candidate, University of Toronto

Risa Ulinski

PhD Candidate, University of Toronto

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