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About

Fanjun Bu investigates how robots integrate into human-centered environments, focusing on bimanual manipulation, human-robot interaction in public spaces, and assistive robotics. Their early work introduced a benchmark for bimanual robotic manipulation of semi-deformable objects (37 citations), drawing from watchmaking and automotive assembly to evaluate dexterous coordination. Bu’s most impactful research examines emergent interactions between people and autonomous trash barrel robots deployed in New York City plazas. Through video analysis of these in-the-wild deployments, Bu revealed how movement-based practices and sensemaking unfold when robots become part of public life (23 citations for "Trash in Motion"). Their methodological contributions include critical reflections on the Wizard-of-Oz technique, analyzing the hidden labor of human operators behind autonomous systems. Bu also advances assistive robotics, developing data-driven models for bite timing prediction during social dining to enable robot-assisted feeding for people with mobility limitations. This work bridges technical innovation with real-world social dynamics, demonstrating how robots can navigate urban streets harmoniously—a concept Bu formalized as the "Robotability Score." Their research offers essential insights for designing robots that coexist gracefully with people in shared spaces.