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About

Ruixiang Deng is a robotics researcher whose work bridges the critical gap between tactile sensing and computer vision for intelligent robotic manipulation. His research focuses on capacitive tactile sensors, electrical capacitance tomography (ECT) for grippers, and real-time instance segmentation. Deng made a pioneering contribution by being the first to explore ECT sensor application in robotic grippers, demonstrating how electrode configurations affect imaging quality for symmetrical gripping tasks. He also developed FRISNET, a fast real-time instance segmentation network that fuses frequency domain and spatial features to improve location accuracy in complex environments. Additionally, Deng advanced physically-grounded 3D point cloud processing by integrating tactile sensor specifications to enhance filtering and clustering for unstructured environments. His most-cited works—including evaluations of capacitive tactile sensor materials and ECT gripper designs—have each garnered 2 citations, reflecting early recognition in the field. Deng’s work is notable for its practical focus on enabling robots to perceive and adjust grip force through tactile data, a crucial capability for safe and effective manipulation in real-world settings.