Botao He
Botao He is a PhD student in Computer Science at the University of Maryland, College Park, where his research focuses on interactive perception and learning, dexterous manipulation, and event-camera-based robotics. He is best known for his work on the FEEL (Force-Enhanced Egocentric Learning) dataset, which captures surface electromyography signals from a wearable wristband to estimate per-finger forces for human demonstration learning. He has also published on event-based 3D Gaussian splatting for robot egomotion, aerial navigation, and active human pose estimation via autonomous UAV agents. He has held a research internship at Amazon FAR and was previously a research assistant at the FAST Lab at Zhejiang University.
“The core contribution is a $300 wristband that captures surface electromyography (sEMG) signals from the forearm and converts them into per-finger force estimates, enabling force-enriched human demonstrations without instrumenting the fingertips.”
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