Lingtong Kong

Shandong University of Science and Technology

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About

Lingtong Kong is a pioneering researcher in neuromorphic engineering and bio-inspired computing, with a focus on bridging the gap between artificial neural circuits and biological learning mechanisms. His major contributions center on developing memristive neuromorphic circuits that emulate classical and operant conditioning—fundamental forms of associative learning in living organisms. Unlike conventional approaches that prioritize functional replication, Kong’s work uniquely emphasizes biomimetic circuit structures and operational rules, enabling systems that learn, memorize, and make decisions more akin to biological neural networks. His highly cited 2024 paper, “Neuromorphic Circuit of Classical and Operant Conditioning Based on Tunable Neural Circuitry Motifs,” has garnered 18 citations, reflecting its impact on advancing hardware-based artificial intelligence. By integrating tunable neural circuitry motifs, Kong’s research offers a pathway toward more adaptive, energy-efficient neuromorphic systems, with potential applications in robotics, edge computing, and brain-machine interfaces. His work stands out for its innovative synthesis of neuroscience principles and circuit design, positioning him as a key contributor to next-generation intelligent hardware.