Shanghai Jiaotong University - China
AUTHOR PROFILR
ORCID
EARLY ACADEMIC PURSUITS:
Zicheng Huang embarked on his academic journey in 2016, earning a bachelor's degree from the University of Electronic Science and Technology of China. This laid the groundwork for his Ph.D. pursuit at Shanghai Jiao Tong University, where he delved into Computational Imaging and Scattering Imaging, exhibiting a keen interest in cutting-edge optical technologies.
PROFESSIONAL ENDEAVORS:
Currently a Ph.D. student at Shanghai Jiao Tong University, Zicheng's professional trajectory showcases a transition from the University of Electronic Science and Technology of China to pursuing a Ph.D. at Shanghai Jiao Tong University. This transition signifies a commitment to advancing his expertise in computational and scattering imaging.
CONTRIBUTIONS AND RESEARCH FOCUS:
Zicheng Huang's research focus is in Computational Imaging, Scattering Imaging, and Optical Neural Networks. His endeavors concentrate on addressing challenges in deep learning methods, particularly in imaging through scattering media. Notably, he strives to mitigate computational costs and power consumption challenges associated with current deep learning techniques, emphasizing the modeling of scattered light fields.
IMPACT AND INFLUENCE:
Zicheng's impact is evident through his pioneering research in optronic convolutional neural networks. These innovations significantly contribute to imaging through scattering media, reducing power consumption by over 70% and computational costs by more than 98.5%, surpassing current state-of-the-art methods. His publications in reputable journals, including Optics Express and Optics and Lasers in Engineering, underscore the influence of his work in the scientific community.
ACADEMIC CITES:
Zicheng Huang's research findings are well-recognized in the academic community, as evidenced by his publications in esteemed journals. His work, including "OP-FCNN: an optronic fully convolutional neural network for imaging through scattering media," has been acknowledged in journals with notable impact factors, such as Optics Express (JCR Q2).
LEGACY AND FUTURE CONTRIBUTIONS:
As a young researcher, Zicheng Huang's legacy is poised to revolve around advancements in opto-electronic deep learning. His innovative approaches to address challenges in artificial neural networks signal a promising future in the field. His commitment to low-power consumption and efficient computational methods positions him as a key contributor to the intersection of optics and neural networks.
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