Refreshments are available starting at 10:30 a.m. The seminar will begin at 10:45 a.m.
Abstract
Computer graphics research has long been dominated by the interests of large film, television, and social media companies, forcing other, more safety-critical applications (e.g., medicine, engineering, security) to repurpose graphics algorithms originally designed for entertainment. In this talk, Silvia Sellán will advocate for a perspective shift in this field that allows researchers to design algorithms directly for these safety-critical application realms. She will show that this begins by reinterpreting traditional graphics tasks (e.g., 3D modeling and reconstruction) from a statistical lens and quantifying the uncertainty in algorithmic outputs, as exemplified by the research she has conducted for the past five years. She will end by mentioning several ongoing and future research directions that carry this statistical lens to entirely new problems in graphics and vision and into specific applications.
Speaker Biography
Sellán is a fifth-year computer science PhD student at the University of Toronto, working in computer graphics and geometry processing. She is a Vanier Doctoral Scholar, an Adobe Research Fellow, and the winner of the 2021 University of Toronto Arts & Science Dean’s Doctoral Excellence Scholarship. She has interned twice at Adobe Research and twice at the Fields Institute of Mathematics. She is also a founder and organizer of the Toronto Geometry Colloquium and a member of the ACM Community Group for Women in Computer Graphics Research.