Published multiple papers, including 'Memory-Maze: Scenario-Driven Benchmark and Visual Language Navigation Model for Guiding Blind People' (under review) and 'TBD Pedestrian Data Collection: Towards Rich, Portable, and Large-Scale Natural Pedestrian Data' (ICRA 2024). Organized several workshops, such as the 'Unsolved Problems in Social Navigation' workshop at RSS2024.
Research Experience
Currently a postdoc researcher at Miraikan Accessibility Lab in Tokyo, Japan, advised by Chieko Asakawa. Was a member of the TBD lab during his PhD.
Education
PhD from the Robotics Institute, Carnegie Mellon University (December 2023), advised by Aaron Steinfeld.
Background
Research areas include Robotics, Perception, Human-Robot Interaction, and Machine Learning. Focused on solving the social navigation problem, i.e., how a robot can navigate efficiently and safely around humans while conforming to various social rules in pedestrian-rich environments.
Miscellany
Developed various tools and datasets, such as the TBD Pedestrian Dataset and SocNavBench.