Thesis topic: scaling robotic mapping and localization to larger unknown environments. Proposed a sparse information filter algorithm, ESEIF, which maintains estimate consistency and reduces computational and memory costs. Published in IJRR.
Research Experience
Before joining TTI-Chicago, he was a research scientist at the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT, working with Seth Teller. Currently, an associate professor and director of RIPL at TTI-Chicago.
Education
PhD from the Joint Program between MIT and Woods Hole Oceanographic Institution, supervised by John Leonard.
Background
Research interests: computer vision, natural language understanding, and machine learning in the context of robotics. Brief bio: Associate Professor at Toyota Technological Institute at Chicago (TTI-Chicago) and director of the Robot Intelligence through Perception Laboratory (RIPL).
Miscellany
Personal interest: developing intelligent, perceptually aware robots that can act robustly and effectively in unstructured environments, particularly with and alongside people.