Prof. Zhao Zhang, Hefei University of Technology, China

Zhao Zhang, PhD, is a Professor and Doctoral Supervisor who currently serves as the Director of the Department of Intelligent Science and Technology at Hefei University of Technology. He is also an Outstanding Member of CCF and an Advanced Member of IEEE. With an impressive H-Index of 42, Zhao has successfully led three National Natural Science Foundation projects, in addition to receiving prestigious accolades such as the Anhui Province Outstanding Youth Project and the Jiangsu Province Major Natural Science Research Project in Universities.

Zhao's outstanding contributions have been recognized with titles such as "Top Six Talent Peaks" in Jiangsu Province, as well as being selected as an "Outstanding Young Backbone Teacher Training Object of Jiangsu Province's Blue and Blue Project". Furthermore, he has been honored twice with the title of Excellent Master's Thesis Guidance Teacher of Jiangsu Province. It is worth noting that Zhao was recently included in the 2022 Global Top 2% Scientists List released by Stanford University in the United States, where he ranked within the top 0.7% globally in the field of artificial intelligence and image processing.

Research Area: Machine learning, computer vision and pattern recognition, image restoration and enhancement, image and video generation, visual analysis and understanding, and other thematic directions.

Prof. Haiquan Zhao, Southwest Jiaotong University, China

Haiquan Zhao, an IEEE Senior Member, was born in Henan Province, China. He obtained his B.S. degree in applied mathematics in 1998 and went on to complete his M.S. and Ph.D degrees in signal and information processing at Southwest Jiaotong University, Chengdu, China, in 2005 and 2011 respectively.

Since August 2012, he has been serving as a Professor at the School of Electrical Engineering at Southwest Jiaotong University, Chengdu, China. In addition to this role, from 2015 to 2016 he worked as a visiting scholar at the University of Florida, USA.

Prof. Zhao's current research interests include adaptive filtering algorithms, adaptive networks,

nonlinear active noise control, information theoretical learning, adaptive Volterra filter, Kernel adaptive filter,and nonlinear system identification.

He is also the author or coauthor of more than 140 international journal papers indexed by SCI (Science Citation Index), and holds ownership of 70 invention patents.

Furthermore Prof. Zhao has actively served as a reviewer for several IEEE Transactions,IET series,and Signal Processing along with other international journals.He also had experience being the handling editor for Signal Processing(a Top Journal).

Research Area:Intelligent Signal Processing, Pattern recognition and intelligent systems, Electrical engineering.

Prof. Chuan Qin, University of Shanghai for Science and Technology, China

Chuan Qin received his B.S. degree in electronic engineering and the M.S. degree in signal and information processing from Hefei University of Technology, Anhui, China, in 2002 and 2005, respectively, and the Ph.D. degree in signal and information processing from Shanghai University, Shanghai, China, in 2008. Since Dec. 2008, he has been with the faculty of University of Shanghai for Science and Technology, where he is currently a Professor. He was with Feng Chia University at Taiwan as a Postdoctoral Researcher from July 2010 to July 2012. His research interests include multimedia intelligent computing, AI security, data hiding and image processing in encrypted domain. He has published over 200 peer-reviewed papers in journals and conferences, such as IEEE TIP, IEEE TIFS, IEEE TMM, IEEE TCSVT, IEEE TDSC, IEEE TETCI, IEEE TIM, IEEE TAI and ACM MM. He has also published one book and held six authorized patents. He was selected as the Highly Cited Chinese Researchers by Elsevier in 2020 and the World’s Top 2% Scientists in 2019-2022. He won the Excellent Paper Awards of CIHW 2016 and ChinaMFS 2023, and the Candidate of Excellent Paper Award of IEEE IIHMSP 2014. He has served as the Associate Editor for ACM TOMM, Signal Processing (Elsevier) and Information Fusion (Elsevier). 

Research Area: Multimedia intelligent computing, AI security, deep learning, digital image processing, etc.

Prof. Hui-Yu Zhou, University of Leicester, UK

Prof. Huiyu Zhou received a Bachelor of Engineering degree in Radio Technology from Huazhong University of Science and Technology of China and a Master of Science degree in Biomedical Engineering from University of Dundee of United Kingdom, respectively. He was awarded a Doctor of Philosophy degree in Computer Vision from Heriot-Watt University, Edinburgh, United Kingdom, supervised by Professors Patrick Green (Psychology) and Andrew Wallace (Computer Engineering).Prof. Zhou heads the Applied Algorithms and AI (AAAI) Theme and leads the Biomedical Image Processing Lab (BIPL) at University of Leicester. He was Director of MSc Programme (2018-2019) and Coordinator of MSc Distance Learning at Informatics (2018-2022), and is PGR Director and Deputy Director of Research Centre for Artificial Intelligence, Data Analytics and Modelling (AIDAM). Prior to this appointment, he worked as Reader (2018-2020) at University of Leicester, and Lecturer (2012-2017) at the School of Electronics, Electrical Engineering and Computer Science, Queen's University Belfast (QUB). He was a visiting scholar of QUB during 2018-2020.

Research Area: Prof. Zhou's research specialisation includes machine learning, computer vision, intelligent systems and signal processing. His research interest has focused on the development of AI/machine learning algorithms that enable a system to better understand and interpret images/signals.

Prof. Yajun Liu, South China University of Technology, China

Prof. Yajun Liu is currently a professor at the School of Mechanical and Automotive Engineering at South China University of Technology.

From December 2009 to December 2010, Prof. Liu was a visiting professor at the Fluid Dynamics Research Center (FPRC) at Purdue University in the United States.

From February 2005 to July 2016, Prof. Liu worked as a postdoctoral researcher at Tokheim Joint Venture in China.

Prof. Liu obtained a PhD in Mechanical Engineering from South China University of Technology, Guangzhou, China in June 2002.

His main research direction includes digital signal processing technology and its application in mechanical systems (such as energy-saving in hydraulic systems), Intelligent Control, and Manufacturing Engineering. Additionally, Professor Liu has published over 250 papers in international conference journals and collections of papers, as well as more than 40 patents for mechanical system design and manufacturing.

Research Area: Digital signal processing technology and its application in mechanical systems (such as energy-saving in hydraulic systems); Intelligent control and manufacturing engineering, etc.

Prof. Lei Chen, Shandong University, China

Chen Lei, Ph.D./Postdoctoral, is an Associate Professor and Master's Supervisor at the School of Information Science and Engineering, Shandong University. He obtained his PhD from the School of Electronic Engineering and Computer Science at the University of Ottawa in Canada, and holds a bachelor's and master's degree from the School of Information Science and Engineering at Shandong University. Chen Lei is also recognized as a Shandong University Youth Scholar Future Plan member and a member of the China Association of Automation.

His primary research areas include image processing and computer vision, digital watermarking and visual quality assessment, as well as machine learning and artificial intelligence. Currently, he oversees projects funded by the National Natural Science Foundation of China, sub-projects of the National Key Research and Development Program, the Shandong Provincial Natural Science Foundation, and the China Postdoctoral Fund. In addition to these responsibilities, Chen Lei has been involved in numerous national-levels scientific research projects including those supported by Canadian Science and Engineering Research Fund.

Research Area: Image processing and computer vision, digital watermarking and visual quality assessment, as well as machine learning and artificial intelligence.