Cao Changqing | Intelligent Perception | Best Researcher Award

Published on by China Scientist

Prof. Cao Changqing | Intelligent Perception | Best Researcher Award 

Prof. Cao Changqing is a researcher at Xidian University specializing in optoelectronic technology, remote sensing, and artificial intelligence image processing. He earned his bachelor’s, master’s, and doctoral degrees in optical engineering from Xidian University and has since dedicated his career to advancing research and teaching in optoelectronics engineering. His work has gained international recognition, including being listed among the top global scientists. He has published widely in leading journals and serves as both reviewer and editor for renowned publishers in optics and photonics. His research focuses on optical imaging algorithms, interferometric techniques, laser dynamics, and phase compensation methods, contributing to the progress of modern optoelectronic science and technology.

Prof. Cao Changqing | Xidian University | China

Profiles

SCOPUS

ORCID

Education

  • Cao Changqing pursued his academic journey entirely at Xidian University, where he built a strong foundation in optical engineering. He advanced from undergraduate to postgraduate studies, ultimately completing his doctoral degree in the same discipline. His long-term academic engagement at the same institution reflects both dedication and a deepening of expertise in the field of optoelectronics.

Experience

  • After completing his education, Prof. Cao continued his career at Xidian University, where he has been engaged in teaching and research in optoelectronics engineering. His role has centered on advancing innovations in optical technologies, remote sensing, and artificial intelligence in image processing. Over the years, he has guided scientific inquiry and contributed significantly to the academic and research environment of the institution.

Awards and Recognition

  • Prof. Cao has earned global recognition for his research contributions, being listed among the top global scientists in recent editions of a prestigious ranking. His achievements demonstrate the international impact of his work and highlight his role as a leading scholar in his areas of expertise.

Skills and Expertise

  • Prof. Cao possesses extensive skills in optoelectronic technology, remote sensing systems, and artificial intelligence image processing. His proficiency extends to advanced imaging algorithms, optical communication techniques, and laser dynamics. He is also highly skilled in scientific publishing and reviewing, serving as a reviewer for well-known international journals and as an editor for respected publications in optics and photonics.

Research Focus 

  • The core of Prof. Cao’s research is centered on advancing optoelectronics, remote sensing, and artificial intelligence image processing. His studies explore optical imaging algorithms, interferometric techniques, and the dynamic characteristics of lasers. He also works on innovations in phase compensation methods, photon-integrated imaging, and polarimetric scattering phenomena, ensuring his contributions remain at the forefront of technological development.

Publication

  • Investigation polarimetric scattering of light from the randomly rough surface based on the calculation of the Mueller matrix
    Author: Song B., Cao C., Feng Z., Wu Z., Yu C., Wei R
    Journal: Optics Express

  • Calibration of SOI Optical Phased Arrays via Improved SPGD Algorithm
    Author: Wang Z., Wu B., Liao J., Li X., Wang C., Sun Y., Jin L., Feng J., Cao C.
    Journal: Optics and Laser Technology, 2023

  • Factors Influencing the Performance of Optical Heterodyne Detection System
    Author: Wu Z., Cao C., Feng Z., Ye S., Li M., Song B., Wei R.
    Journal: Optics and Lasers in Engineering, 2023

  • Improving Distance Imaging Accuracy through Temporal Position Correction with Phase Difference Compensation
    Author: Wu Z., Cao C., Feng Z., Wu X., Duan C., Liu H.
    Journal: Applied Optics, 2023

  • Innovative OPA-based Optical Chip for Enhanced Digital Holography
    Author: Wang Z., Linke Liu, Jiang P., Liao J., Jiamu Xu, Yanling Sun, Ji’n Li, Zhenzhong Lu, Feng J., Cao C.
    Journal: Optics Express, 2023

Conclusion

  • Prof. Cao Changqing is an accomplished scholar whose career combines education, research, and service in the field of optoelectronics. His strong academic background, professional contributions, and international recognition underline his influence in advancing both theoretical and applied aspects of optical engineering and remote sensing. Through his innovative research and editorial service, he continues to shape the future of optical science and technology.

Yuan Cheng | Medical Imaging | Best Researcher Award

Published on by China Scientist

Prof. Dr. Yuan Cheng | Medical Imaging | Best Researcher Award

Yuan Cheng is a Professor at the AI Innovation and Incubation Institute, Fudan University, specializing in artificial intelligence for science, computer vision, video analysis, and medical image processing. He earned his Ph.D. in Computer Science from the National University of Singapore and a B.S. from Fudan University. With over a decade of experience, he has held roles as a Research Fellow, Scientist, and Tech Lead, contributing to disease detection systems, video-based AI solutions, and craniomaxillofacial surgery planning. Yuan holds 36 granted patents, has won multiple AI and fintech awards, and continues to advance interdisciplinary applications of AI in medicine and technology.

Prof. Dr. Yuan Cheng | Fudan University | China

Profile

SCOPUS ID

🎓 Education

  • Yuan Cheng holds a Ph.D. in Computer Science from the National University of Singapore (NUS), earned between August 2008 and April 2014. His doctoral dissertation, titled Computer-Aided Craniomaxillofacial Surgery Planning for Fractured Skulls, was supervised by Professor Leow Wee Kheng. Prior to this, he completed a Bachelor of Science in Computer Science and Technology at Fudan University, Shanghai, China, from September 2004 to July 2008. His undergraduate dissertation focused on Low Resolution Gait Recognition with High Frequency Super Resolution, under the guidance of Professor Zhang Junping.

💼 Experience

  • Yuan Cheng is currently a Professor at the AI Innovation and Incubation Institute (AI3) at Fudan University, China, where he has been serving since September 2022. His research emphasizes leveraging artificial intelligence for science, including applications in biology, pharmacy, and medicine. From October 2016 to August 2022, he worked as a Staff Algorithm Engineer, Tech Lead, and Manager at the AI Department of Ant Group, China. In this role, he led a vision cognition team that developed advanced technologies for video analysis, edge computing, and affective computing, which were implemented in products such as automatic car damage assessment and pet recognition systems. Before this, he was a Research Fellow and Team Leader at the iLab of the National University of Singapore from August 2012 to October 2016, focusing on algorithms for detecting and managing diseases like glaucoma, diabetes, and hypertension. Yuan Cheng also contributed as a Research Scientist at the National University Hospital, Singapore, from August 2013 to May 2015, where he developed systems for skull restoration and stroke severity assessment. Earlier in his career, he served as a Research Assistant at the Shanghai Key Laboratory of Intelligent Information Processing from September 2005 to July 2008, working on super-resolution methods for gait recognition.

 🏆 Honors and Awards

  • Yuan Cheng has been recognized with numerous awards throughout his career. He was honored as a Hangzhou High-level Talent (D class) in 2021 and secured first-place finishes in several prestigious competitions, including the Valence-Arousal Estimation Challenge at CVPR 2022 and multimodal challenges at ACM MM 2021. His team achievements include the Green Eyes Award by the United Nations in 2019 and multiple innovation and application awards in artificial intelligence and fintech from 2017 to 2019. He was a recipient of the Singapore Technology Award (team) in 2014 and was awarded the NUS Graduate Research Scholarship during his doctoral studies. Additionally, he earned numerous scholarships and accolades during his undergraduate years, including the Chinese Excellent Student award by IBM in 2008 and the Wangdao Scholarship at Fudan University.

🛠️ Skills and Certifications

  • Yuan Cheng is skilled in advanced computer vision techniques, machine learning algorithms, video and medical image analysis, edge computing, and affective computing. His technical expertise is complemented by his experience in developing real-world applications for various industries, including healthcare and financial technology. Additionally, he holds 36 granted patents and has applied for 68 more, showcasing his innovation in cutting-edge technologies.

🔬 Research Focus

  • Yuan Cheng’s research interests span artificial intelligence for science, computer vision, video analysis, medical image analysis, and machine learning. He has made significant contributions to areas such as craniomaxillofacial surgery planning, disease detection systems, and video-based financial technologies. His current work emphasizes integrating AI innovations into biology, pharmacy, and medicine, bridging interdisciplinary gaps to foster impactful solutions.

Conclusion

  • Yuan Cheng is a strong candidate for the Best Researcher Award due to his exceptional accomplishments in AI research, applied innovation, and impactful solutions. He exemplifies the qualities of a top researcher: innovative thinking, societal impact, and global recognition. Enhancing his academic outputs and broader collaborations could further solidify his eligibility and chances for this award.

📄Publications

  • Enhancing Personalized Headline Generation via Offline Goal-conditioned Reinforcement Learning with Large Language Models
    Authors: Tan, X., Cheng, L., Qiu, X., Xu, Y., Qi, Y.
    Journal: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2024
  • Enhancing Task Performance in Continual Instruction Fine-tuning Through Format Uniformity
    Authors: Tan, X., Cheng, L., Qiu, X., Xu, Y., Qi, Y.
    Journal: SIGIR 2024 – Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024
  • SNP-S3: Shared Network Pre-Training and Significant Semantic Strengthening for Various Video-Text Tasks
    Authors: Dong, X., Guo, Q., Gan, T., Cheng, Y., Chu, W.
    Journal: IEEE Transactions on Circuits and Systems for Video Technology, 2024
  • Unraveling the Motion and Deformation Characteristics of Red Blood Cells in a Deterministic Lateral Displacement Device
    Authors: Liu, S., Chen, S., Xiao, L., Hu, Z., Lin, C.
    Journal: Computers in Biology and Medicine, 2024
  • FuXi: A Cascade Machine Learning Forecasting System for 15-Day Global Weather Forecast
    Authors: Chen, L., Zhong, X., Zhang, F., Qi, Y., Li, H.
    Journal: npj Climate and Atmospheric Science, 2023