Time: Monday, March 27, 2017, 1:00pm @ MTH3206

Speaker: Michael Robinson (American University)

Title: Topological sensor data fusion

Abstract: A sensor integration framework should be sufficiently general to accurately represent many sensor modalities, and also be able to summarize information in a faithful way that emphasizes important, actionable information. Few approaches adequately address these two discordant requirements. The purpose of this talk is to explain why sheaves are a convenient data structure for sensor integration and how the mathematics of sheaves satisfies our two requirements. We outline some of the powerful inferential tools that are not available to other representational frameworks.