Qingyan Li
Papers
3
Total Citations
30
H-Index
2
About
Qingyan Li is a researcher at the forefront of neuromorphic computing and advanced optical systems, whose work bridges the gap between artificial intelligence hardware and autonomous sensing technologies. Her most impactful contribution lies in developing a resistive switching memory (RRAM) based on a polyvinyl alcohol-graphene oxide hybrid material, which not only achieves high-density storage but also mimics neural synapses for visual perception nervous systems—a breakthrough with 24 citations that paves the way for brain-inspired AI. In the field of LiDAR, Li has designed innovative optical systems to overcome critical challenges: a receiving system with a large field of view and high light concentration to resist background interference (5 citations), and a transmitting system for large-angle MEMS LiDAR achieving high spatial resolution (1 citation). These designs enhance detection reliability in autonomous driving, robotics, and remote sensing. Li’s work demonstrates a rare ability to integrate materials science with optical engineering, producing tangible solutions for next-generation intelligent systems. Her research is essential reading for those exploring neuromorphic devices and high-performance LiDAR.
Research Focus
Key Achievements
Top Papers
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