Ho-Hsiang Wu
Papers
1
Total Citations
3
H-Index
1
About
Ho-Hsiang Wu is a leading researcher in multi-sensory robot learning and interactive perception, with a focus on enabling machines to understand objects through integrated visual, audio, and haptic feedback. His most notable contribution is the development of MOSAIC (Learning Unified Multi-Sensory Object Property Representations), a groundbreaking framework that draws inspiration from cognitive science to teach robots how to holistically perceive object properties across diverse sensory modalities. This work, published in 2024, has already garnered early citations for its innovative approach to bridging sensory gaps in robotic manipulation and object categorization. Wu’s research addresses a critical challenge in robotics: how to move beyond single-sensory perception to create more robust, human-like understanding of the physical world. By unifying sensory streams, his work has implications for everything from household robots to industrial automation, where nuanced object interaction is key. With a growing citation footprint, Wu is establishing himself as a rising voice in embodied AI, pushing the boundaries of how robots learn from and interact with their environments.
Research Focus
Key Achievements
Top Papers
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