Associate Professor at University of Science and Technology Beijing, China
Assoc. Prof. Dr. Peixian Zhuang is a distinguished researcher in computer vision, machine learning, and underwater image processing. Currently an Associate Professor at the University of Science and Technology Beijing, he earned his Ph.D. from Xiamen University in 2016. With over 50 published papers, including 9 ESI Highly Cited/Hot Papers and over 2800 Google Scholar citations, his work has garnered significant academic influence. Dr. Zhuang has led four national projects, holds six patents, and authored a book, showcasing his commitment to advancing technological innovation. His contributions have been recognized globally, as he was listed among the “World’s Top 2% Scientists” in 2023 and 2024. In addition to his research, he serves as an editor for various esteemed journals and has reviewed over 100 international journals and conferences. His collaborations with institutions like Tsinghua University further underscore his dedication to expanding the boundaries of AI and image processing.
Education
Assoc. Prof. Dr. Peixian Zhuang completed his Ph.D. in 2016 at Xiamen University, where he laid the foundation for his research expertise in computer vision, underwater image processing, and machine learning. Following his doctoral studies, he began his academic career as a Lecturer at Nanjing University of Information Science & Technology (2017-2020), where he further honed his skills and contributed to his fields of study. To deepen his research, Dr. Zhuang undertook postdoctoral training at Tsinghua University (2020-2022), engaging in advanced projects and expanding his expertise in innovative AI technologies. His educational journey has been marked by significant contributions to his field, earning him recognition as a “World’s Top 2% Scientist” in recent years. Dr. Zhuang’s robust academic background has established him as a leading researcher and educator, influencing both national and international advancements in machine learning and image processing.
Professional Experience
Assoc. Prof. Dr. Peixian Zhuang has a diverse professional background in academia and research. Currently serving as an Associate Professor at the University of Science and Technology Beijing, he has made significant contributions to the fields of underwater image processing and machine learning. Prior to this role, he was a Lecturer at Nanjing University of Information Science & Technology from 2017 to 2020, where he developed and delivered courses while conducting impactful research. Following this, Dr. Zhuang completed a postdoctoral fellowship at Tsinghua University (2020-2022), where he engaged in advanced research projects and collaborations with leading scientists. He has led four national research projects and has authored over 50 papers, showcasing his commitment to scientific advancement. In addition to his academic roles, he serves as an area editor and guest editor for various reputable journals, reflecting his expertise and active engagement in the global research community.
Research Interest
Assoc. Prof. Dr. Peixian Zhuang specializes in several cutting-edge areas within the fields of computer vision and machine learning. His primary research interests include underwater image processing, where he focuses on improving the quality and usability of images captured in challenging underwater environments. He employs advanced algorithms and techniques to enhance image clarity and object recognition. Additionally, Dr. Zhuang is deeply invested in Bayesian machine learning, exploring probabilistic models that can improve decision-making processes in uncertain environments. His work on signal sparse representation and deep neural networks further highlights his commitment to developing innovative solutions for complex problems in artificial intelligence. By integrating these methodologies, Dr. Zhuang aims to advance the understanding and application of AI in real-world scenarios. His research not only contributes to theoretical advancements but also has practical implications in fields such as marine science, environmental monitoring, and robotics, making a significant impact on technology and research.
Awards and Honors
Assoc. Prof. Dr. Peixian Zhuang has received numerous awards and honors throughout his academic career, reflecting his significant contributions to research and innovation. He was recognized as one of the “World’s Top 2% Scientists” in both 2023 and 2024, an accolade that highlights his impact and influence in the field of computer vision and machine learning. In 2023, he received the IFAC EAAI Paper Prize Award, underscoring the excellence of his research publications. Additionally, his doctoral dissertation was awarded the Outstanding Doctoral Dissertations of Fujian Province in 2017, recognizing the quality and originality of his work during his Ph.D. studies. Dr. Zhuang has also been involved in various editorial roles for reputable journals, enhancing his recognition as a leading researcher in his field. These awards and honors reflect his dedication to advancing scientific knowledge and his commitment to excellence in research and education.
Conclusion
Peixian Zhuang’s profile makes him a strong candidate for the Best Researcher Award. His influential research, substantial publication record, recognition in global scientific rankings, and engagement in scholarly activities demonstrate his commitment and impact in the field of computer vision and underwater image processing. Addressing the outlined areas of improvement could enhance his profile further, positioning him as a leading researcher capable of impacting both academia and industry.
Publications top noted📜
- Title: A retinex-based enhancing approach for single underwater image
Authors: X Fu, P Zhuang, Y Huang, Y Liao, XP Zhang, X Ding
Year: 2014
Citations: 566
- Title: Underwater image enhancement using a multiscale dense generative adversarial network
Authors: Y Guo, H Li, P Zhuang
Year: 2019
Citations: 420
- Title: Underwater image enhancement via minimal color loss and locally adaptive contrast enhancement
Authors: W Zhang, P Zhuang, HH Sun, G Li, S Kwong, C Li
Year: 2022
Citations: 373
- Title: Bayesian retinex underwater image enhancement
Authors: P Zhuang, C Li, J Wu
Year: 2021
Citations: 255
- Title: Underwater image enhancement with hyper-laplacian reflectance priors
Authors: P Zhuang, J Wu, F Porikli, C Li
Year: 2022
Citations: 250
- Title: Underwater image enhancement using an edge-preserving filtering retinex algorithm
Authors: P Zhuang, X Ding
Year: 2020
Citations: 93
- Title: Underwater image enhancement via weighted wavelet visual perception fusion
Authors: W Zhang, L Zhou, P Zhuang, G Li, X Pan, W Zhao, C Li
Year: 2023
Citations: 86
- Title: Removing stripe noise from infrared cloud images via deep convolutional networks
Authors: P Xiao, Y Guo, P Zhuang
Year: 2018
Citations: 80
- Title: Underwater image enhancement via piecewise color correction and dual prior optimized contrast enhancement
Authors: W Zhang, S Jin, P Zhuang, Z Liang, C Li
Year: 2023
Citations: 77
- Title: Non-uniform illumination underwater image restoration via illumination channel sparsity prior
Authors: G Hou, N Li, P Zhuang, K Li, H Sun, C Li
Year: 2023
Citations: 54
- Title: CVANet: Cascaded visual attention network for single image super-resolution
Authors: W Zhang, W Zhao, J Li, P Zhuang, H Sun, Y Xu, C Li
Year: 2024
Citations: 49
- Title: DewaterNet: A fusion adversarial real underwater image enhancement network
Authors: H Li, P Zhuang
Year: 2021
Citations: 49
- Title: SSTNet: Spatial, spectral, and texture aware attention network using hyperspectral image for corn variety identification
Authors: W Zhang, Z Li, HH Sun, Q Zhang, P Zhuang, C Li
Year: 2022
Citations: 45
- Title: Bayesian pan-sharpening with multiorder gradient-based deep network constraints
Authors: P Guo, P Zhuang, Y Guo
Year: 2020
Citations: 41
- Title: GIFM: An image restoration method with generalized image formation model for poor visible conditions
Authors: Z Liang, W Zhang, R Ruan, P Zhuang, C Li
Year: 2022
Citations: 37
