Chuanqing Wang

  • 2019 B.S. Harbin Engineering University



Chuanqing WANG received the B.S. degree in material science and engineering from Harbin Engineering University, Harbin, China. He participated in summer program of Neuroscience and Cognitive Science in Tsinghua-Peking University. He joined the Center of Excellence in Biomedical Research on Advanced Integrated-on-chips Neurotechnologies (CenBRAIN Neurotech) and became a PhD Candidate of Westlake University in September 2019.

Research Interests and Project 

Retinal prostheses are intended to enhance vision in individuals suffering from retinal impairments such as Age-related Macular Degeneration (AMD) and Retinitis Pigmentosa (RP). Intelligent and low-power retinal prostheses are highly demanded in this era, where wearable and implantable devices are used for numerous healthcare applications. To stay current and address this challenge, we propose a bio-inspired power-efficient optogenetics-based retinal prostheses. This approach utilizes a spike-based processing framework that mimics the behavior of the human retina and replaces the function of degenerative cell layers. This algorithm is being implemented on a custom neuromorphic processor to meet the criteria for real-time processing and low-power consumption. This optogenetic-based retinal prosthesis with bio-inspired processing framework as well as power efficient characteristics will provide a promising solution for improving vision restoration in both AMD and RP.

Representative Publications

[1] Wang C, Fang C, M. Sawan, et al. “Artificial intelligence techniques for retinal prostheses: A comprehensive review and future direction”. Journal of Neural Engineering, 2023, doi: 10.1088/1741-2552/acb295.

[2] C. Wang, J. Yang and M. Sawan, "NeuroSEE: A Neuromorphic Energy-Efficient Processing Framework for Visual Prostheses," in IEEE Journal of Biomedical and Health Informatics, vol. 26, no. 8, pp. 4132-4141, Aug. 2022, doi: 10.1109/JBHI.2022.3172306. (Journal cover)

[3] Wang C, Fang C, M. Sawan, et al. SpikeSEE: An Energy-Efficient Dynamic Scenes Processing Framework for Retinal Prostheses. arXiv preprint arXiv:2209.07898, 2022.

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