Events Calendar

CS Colloquium: Justin Solomon (Stanford) - Embracing Uncertainty in Geometric Data Analysis

Speaker: Justin Solomon, Stanford University

Talk Title: Embracing Uncertainty in Geometric Data Analysis

Series: CS Colloquium

Abstract: Many methods dealing with data on geometric domains suffer from noise, nonconvexity, and other challenges because they are forced to make choices among nearly-indistinguishable possibilities. For instance, edge-preserving image filters must assign pixels near the boundary of an object to either its interior or its exterior, inheriting different colors, textures, and other properties depending on the particular outcome. In geometry processing, algorithms for registering scans of three-dimensional objects must break discrete (e.g. left-right) and continuous (e.g. cylindrical or translational) symmetries to settle on a single correspondence.

In this talk, I will present techniques for explicitly acknowledging these and other ambiguities within graphics, imaging, and data processing pipelines. In particular, rather than making arbitrary tie-breaking decisions, these methods maintain distributions over potential outcomes. This “soft” probabilistic framework explicitly acknowledges challenging ambiguities and can be used to design robust techniques for processing and understanding images and shapes. In addition to introducing the relevant theory, I will show how it can be used to derive practical algorithms for photo processing, network analysis, and surface mapping.

Biography: Justin Solomon is a PhD candidate in the Geometric Computing Group at Stanford University. He studies problems in graphics, learning, and imaging combining techniques from mathematical theory and computer science. His work has led to practical applications in geometry processing, computational photography, and medical imaging and is supported by the Hertz Foundation Fellowship, the NSF Graduate Research Fellowship, and the NDSEG Fellowship.

Justin holds bachelors degrees in mathematics and computer science and a masters degree in computer science from Stanford. He is a dedicated instructor and has served as the lecturer for courses in graphics, differential geometry, and numerical methods. His forthcoming textbook entitled Numerical Algorithms focuses on applications of numerical methods to graphics, learning, and vision. Before beginning his graduate studies, Justin was a member of Pixar's Tools Research group. Outside the lab, he is a pianist, cellist, and amateur musicologist with award-winning research on early recordings of the Elgar Cello Concerto.

Host: Fei Sha

Location: Henry Salvatori Computer Science Center (SAL) - 101

Audiences: Everyone Is Invited

Contact: Assistant to CS chair