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About

Minwoo Jung is a robotics and autonomous systems researcher whose work centers on LiDAR-based perception, robot localization, and sensor fusion. His most significant contribution is a comprehensive survey on LiDAR odometry — a foundational problem in robot navigation involving accurate motion estimation without reliance on GPS — which has garnered over 106 citations since its 2024 publication, establishing it as a key reference in the field. Jung has also made notable strides in place recognition, developing the HeLiPR dataset, a large-scale heterogeneous LiDAR benchmark designed to advance inter-LiDAR localization across diverse spatiotemporal conditions, which has attracted 47 citations. His research further extends into novel sensing modalities, including the TRansPose dataset, which leverages thermal infrared cameras to tackle the notoriously difficult problem of transparent object recognition — an area where conventional RGB and depth sensors fall short. His most recent work, Helios, introduces a spherical transformer-based approach to broaden place recognition beyond traditional spinning LiDARs. Collectively, Jung's contributions reflect a consistent drive to push the boundaries of robust robot perception across heterogeneous sensor environments.