Hao Kang

Papers

Total Citations

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About

Hao Kang is a researcher whose work bridges computer vision, robotics, and human-computer interaction, with a particular focus on enabling machines to understand and interact with dynamic physical and social environments. His research explores how robots can perceive, interpret, and respond to complex real-world scenarios, from object manipulation to autonomous photography. Kang’s most cited work, "Understanding and Exploiting Object Interaction Landscapes" (2017), introduces a novel framework for encoding the motion signatures of human-object interactions. By capturing and comparing interaction trajectories, this work provides a foundational method for robots to understand how humans manipulate objects—a critical step toward more intuitive human-robot collaboration. In "LeRoP: A Learning-Based Modular Robot Photography Framework" (2019), Kang tackles the challenge of autonomous portrait photography. The framework integrates person re-identification with real-time compositional adjustment, allowing a robot to follow a subject and autonomously frame aesthetically pleasing shots. This work demonstrates a practical application of computer vision and robotics in creative domains. With each paper garnering 3 citations, Kang’s contributions are notable for their conceptual clarity and interdisciplinary approach, laying groundwork for future systems that can both understand physical interactions and engage in socially intelligent tasks.