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About

Weicong Sng is a leading researcher in neuromorphic tactile sensing and event-driven perception for robotics. His work centers on developing biologically-inspired tactile sensors and multi-modal learning systems that enable robots to perceive touch asynchronously, much like human skin. Sng’s major contribution is the creation of NeuTouch, a novel neuromorphic fingertip tactile sensor that scales efficiently with the number of taxels thanks to its event-based design. This breakthrough allows for high-resolution, low-latency tactile feedback without the computational burden of traditional sensors. His paper “Event-Driven Visual-Tactile Sensing and Learning for Robots” (2020) has garnered 118 citations, underscoring its impact on the field. Sng also pioneered TactileSGNet, a spiking graph neural network for event-based tactile object recognition, which has been cited 51 times. This work integrates spike-based learning with graph neural architectures, enabling robots to recognize objects through touch with remarkable efficiency. Sng’s research is pivotal for advancing robot grasping and in-hand manipulation, bringing machines closer to human-like dexterity. His achievements highlight a transformative approach to multimodal sensing, blending neuroscience, materials science, and machine learning.