Emerson Sie

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About

Emerson Sie is an emerging researcher at the intersection of wireless sensing, robotics, and computer vision, with a focus on leveraging radio frequency (RF) technologies to solve challenging perception problems. His work explores how mmWave radar and wireless signals can augment or replace traditional optical sensors in scenarios where cameras and LiDAR fall short — such as low-light environments, occluded scenes, or privacy-sensitive settings. His most notable contribution, "Radarize" (2024), advances the state of radar-based simultaneous localization and mapping (SLAM) by introducing generalizable Doppler-based odometry, a significant step toward reliable autonomous navigation using mmWave radar alone. With 13 citations in its debut year, the work has quickly gained traction in the robotics and sensing communities. His earlier project, "RF-Annotate" (2022), demonstrates creative cross-modal thinking — using wireless RFID tags to automatically generate labeled training data for visual object detection, bridging the gap between RF sensing and machine learning pipelines for computer vision. Collectively, Sie's research highlights a compelling vision: that RF signals are not merely communication tools but powerful sensing modalities capable of enhancing robot autonomy and intelligent systems in the real world.