Cherie Ho

Papers

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About

Cherie Ho is a robotics researcher whose work spans autonomous aerial systems, 3D human reconstruction, and semantic scene understanding for robot exploration. Her research addresses some of the most challenging problems at the intersection of computer vision and autonomous navigation, particularly in unstructured, real-world environments. Ho's most recognized contribution, "3D Human Reconstruction in the Wild with Collaborative Aerial Cameras" (2021, 15 citations), demonstrated how coordinated aerial vehicles could reconstruct dynamic human motion outdoors — a significant advance for applications in sports analytics, medicine, and entertainment. This work highlights her ability to bridge multi-agent coordination with complex 3D inference problems. Her more recent research pushes the frontier of autonomous exploration in indoor environments. "MapEx" (2025, 8 citations) introduces probabilistic information gain from global map predictions to help robots navigate structured spaces more intelligently, moving beyond conventional frontier-based methods. Complementing this, "RayFronts" (2025, 2 citations) tackles open-set semantic mapping by unifying within-range and beyond-range observations, enabling robots to build richer environmental understanding in open-world settings. Together, Ho's body of work reflects a coherent research vision: empowering autonomous systems to perceive, reconstruct, and explore complex environments with greater intelligence and adaptability.