Papers
2
Total Citations
72
H-Index
2
About
Yiming Dou is a leading researcher in multimodal machine learning, with a primary focus on integrating tactile sensing with vision and audio to build richer, more human-like AI systems. Her work tackles the fundamental challenge of enabling machines to understand objects through touch, a sense critical for physical interaction. In her highly cited 2024 paper, "Binding Touch to Everything" (48 citations), Dou introduced a novel framework for learning unified multimodal tactile representations, overcoming the difficulties posed by diverse touch sensors and scarce data. This contribution is pivotal for advancing robotic manipulation and embodied AI. She is also the driving force behind the ObjectFolder Benchmark (2023, 24 citations), a comprehensive suite of 10 tasks for multisensory object-centric learning. By creating both a neural benchmark and the real-world ObjectFolder Real dataset—which includes synchronized sight, sound, and touch measurements—Dou provided the research community with essential tools for developing and evaluating models that perceive objects holistically. Her work is foundational for the next generation of robots that can interact with the world as adeptly as humans.
Research Focus
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Top Papers
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