Yibo Dong

University of Shanghai for Science and Technology

Papers

Total Citations

H-Index

About

Yibo Dong is a rising researcher in neuromorphic computing and advanced artificial intelligence hardware, with a focus on developing bio-inspired electronic systems that mimic neural functions. His most-cited work, "Multimodal Artificial Synapses for Neuromorphic Application" (2024, 35 citations), explores the design of artificial synapses capable of parallel in-memory computing and efficient signal transmission, offering a pathway to low-energy, high-speed AI. This research directly addresses the energy bottlenecks of traditional computing architectures, positioning his contributions at the forefront of next-generation intelligent systems. Dong’s work is particularly notable for its emphasis on robotic integration, envisioning artificial synapses as the ideal endpoint for autonomous, energy-efficient machines. By bridging materials science, device engineering, and neural network theory, he is advancing the practical realization of neuromorphic hardware. With a growing citation footprint and a clear trajectory toward impactful applications, Yibo Dong is establishing himself as a key contributor to the future of brain-inspired computing and its real-world deployment in robotics and edge AI.