2025 5th International Conference on Optical Imaging and Image Processing (ICOIP 2025)
Keynote Speakers
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Keynote Speakers




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Jungong Han, Tsinghua University

韩军功,清华大学

Professor Jungong Han is Chair Professor in Computer Vision at the Department of Computer Science, the University of Sheffield, UK. He also holds an Honorary Professorship at the University of Warwick, UK. Previously, he was Chair Professor and Director of Research of the Computer Science department with Aberystwyth University, UK; Data Science Associate Professor with the University of Warwick; and Senior Lecturer in Computer Science with Lancaster University, UK.

Prof. Han has authored 2 edited volumes, and over 200 papers, including 90 in prestigious IEEE/ACM Transactions, and 60+ in CORE A* conferences. He has been an Associate Editor-in-Chief of Elsevier Neurocomputing, an Associate Editor of the IEEE Trans. on Image Processing, IEEE Trans. on Neural Networks and Learning Systems, IEEE Trans. on Circuits and Systems for Video Technology, Elsevier Pattern Recognition, and several others. He is a Fellow of IAPR and a Fellow of AAIA.


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Hongying Meng, Brunel University London  IEEE Senior Member,H-index:39

孟鸿鹰,伦敦布鲁内尔大学

Professor Hongying Meng is with Department of Electronic and Electrical Engineering, Brunel University London. Before joining Brunel, he held research positions in several UK universities including University College London (UCL), University of York, University of Southampton, University of Lincoln, and University of Dundee. He received his Ph.D. degree in Communication and Electronic Systems from Xi’an Jiaotong University and was a lecturer in Electronic Engineering Department of Tsinghua University, Beijing in China.  His research area includes biomedical engineering, computer vision, affective computing, artificial intelligence, neuromorphic computing and Internet of Things. His research is funded by EPSRC, EU Horizon 2020, Royal Academy of Engineering, Royal Society, etc. He has published more than 200 academic papers with more than 6800 citations (Google Scholar h-index 39). He has developed 2 different emotion recognition systems that won AVEC2011 and AVEC2013 international challenge competitions respectively. He is a Senior Member of IEEE and an associate editor for IEEE Transactions on Circuits and Systems for Video Technology (TCSVT) and IEEE Transactions on Cognitive and Developmental Systems (TCDS). and the associate Editors-in-Chief for Digital Twins and Applications by IET. In 2022, He was recognized as one of the AI 2000 Most Influential Scholars by Aminer. 


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Zengmao Wang, Wuhan University

王增茂,武汉大学

Zengmao Wang is an associate professor at the School of Computer Science, Wuhan University, and a doctoral and master's supervisor. He is also a visiting scholar at the Department of Computer Science, Carleton University, Canada. He has been awarded the National Postdoctoral Innovative Talent Support Program and the Hubei Provincial Youth Talent Program. His research mainly focuses on machine learning and image processing under resource constraints (including computing power, data, and storage), covering areas such as large models, image generation, domain generalization, and knowledge distillation. He has made significant application advances in fields like medical image analysis and geoscience perception. In recent years, he has published over 30 papers in prominent journals and conferences, including TNNLS, TKDE, TIP, TCYB, TGRS, TCSVT, CVPR, ECCV, and IJCAI.

He has led one general program and one youth program of the National Natural Science Foundation of China, one key research and development program in Hubei Province, and one general program of the Hubei Provincial Natural Science Foundation. He has also participated in five provincial and above-level projects. He received the Second Prize of Hubei Provincial Natural Science Award (ranking third). He serves as a reviewer for multiple international journals and a program committee member for conferences, including TPAMI, TKDE, TMM, TNNLS, IJCAI, AAAI, ICLR, CVPR, and ICML.