Prof. Jonathan M. Garibaldi

IEEE Fellow

University of Nottingham Ningbo China, China

Jonathan M. Garibaldi (Fellow, IEEE) received the B.Sc. (Hons.) degree in physics from Bristol University, Bristol, U.K., in 1984, and the M.Sc. degree in intelligent systems and the Ph.D. degree in uncertainty handling in immediate neonatal assessment from the University of Plymouth, Plymouth, U.K., in 1990 and 1997, respectively.,He is currently the Head of the School of Computer Science, University of Nottingham, Nottingham, U.K., and leads the Intelligent Modelling and Analysis (IMA) Research Group. The IMA research group undertakes research into intelligent modeling, utilizing data analysis, and transformation techniques to enable deeper and clearer understanding of complex problems. He has made many theoretical and practical contributions in fuzzy sets and systems, and in a wide range of generic machine learning techniques in real-world applications. He has authored/coauthored more than 200 articles on fuzzy systems and intelligent data analysis. His research interests include modeling uncertainty and variation in human reasoning, and in modeling and interpreting complex data to enable better decision-making, particularly in medical domains.,Dr. Garibaldi has been the Editor-in-Chief of IEEE Transactions on Fuzzy Systems (2017–2022). He was regularly in the organizing committees and program committees of a range of leading international conferences and workshops, such as FUZZ-IEEE.

Prof.Mengjie Zhang

IEEE Fellow

Victoria University of Wellington, New Zealand

Professor Mengjie Zhang received his BE and ME respectively in 1989 and 1992 from China and his PhD in Computer Science from RMIT Univerity, Australia in 2000. Since 2000, He has been working as a lecturer then senior lecturer, Associate Professor/Reader, and has now been Professor of Computer Science at Victoria University of Wellington since 2011, New Zealand.

His research lies on Artitificial Intelligence, Machine Learning and Big Data, including evolutionary machine learning, genetic programming and evolutionary computation, automated deep learning and neural networks, transfer learning/multi-task learning and domain adaptation, computer vision and image analysis, scheduling/planning and combinatorial optimisation, statistical/AI modelling and neuro-symbolic systems, multi-modal learning, generative AI and large language models, feature selection/construction and explainanle/interpretable AI, and their applications  to primary industry, climate change, (bio)medical/health, and high-tech/high-value manufacturing,  He has published over 900 academic papers in refereed international journals and conferences, and has over 40,000 citations on Google Scholar. 

Prof.Yiu-ming Cheung

Member of European Academy of Sciences and Arts

IEEE/IAPR/AAAS/ IET/BCS Fellow

Hong Kong Baptist University (HKBU), China

Yiu-ming Cheung is currently a Chair Professor (Artificial Intelligence) of the Department of Computer Science, Dean of Institute for Research and Continuing Education (IRACE), and Associate Director of Institute of Computational and Theoretical Studies in Hong Kong Baptist University (HKBU). He received PhD degree from Department of Computer Science and Engineering at The Chinese University of Hong Kong in 2000, and then joined the Department of Computer Science at HKBU in 2001. He is a member of European Academy of Sciences and Arts, and an IEEE Fellow, AAAS Fellow, IAPR Fellow, IET Fellow, and British Computer Society (BCS) Fellow. He is the awardee of RGC Senior Research Fellow with receiving a fellowship grant of HK$7.8 million over a period of 60 months.

His research interests include machine learning and visual computing, as well as their applications in data science, pattern recognition, multi-objective optimization, and information security. He has published over 300 articles in the high-quality conferences and journals, including TPAMI, TNNLS, TIFS, TIP, TMM, TKDE, TCYB, CVPR, ICML, IJCAI, AAAI, and so on. His four co-authored papers have been selected as ESI Highly Cited Papers (i.e. listed in Top 1% globally in the corresponding discipline). Moreover, he has been granted one Chinese patent and two US patents. Subsequently, the underlying technique of his eye-gaze tracking patent has been successfully applied to develop the first mobile app for fatigue driving detection.

Prof.Chunhua Yang

IEEE Fellow

Central South University (CSU), China

Chunhua Yang, Professor at Central South University (CSU), serves as the Deputy Director of the University Academic Committee and Dean of the Faculty of Information Science. She is a recipient of the National Science Fund for Distinguished Young Scholars, an IEEE Fellow, and a Fellow of the Chinese Association of Automation (CAA). She was selected for the New Century National Hundred, Thousand and Ten Thousand Talent Project.

Prof. Yang is the Director of the Key Laboratory of "Industrial Intelligence and Systems" (Ministry of Education) and leads the National Huang Danian-style Teacher Team.

Her long-term research focuses on complex industrial process control and intelligent manufacturing systems technology. She has authored 3 academic monographs, published over 200 SCI-indexed papers, and been granted more than 100 Chinese national invention patents. Her awards include the Third National Innovation Competition Award, 1 Second Prize of the National Technology Invention Award, and 3 Second Prizes of the National Science and Technology Progress Award.

She serves on the editorial boards of journals including IEEE Transactions on Industrial Electronics and IEEE/ASME Transactions on Mechatronics.

Additionally, she holds the positions of Vice Chair of IFAC TC6.2 (Mining, Mineral and Metal Processing) within the International Federation of Automatic Control (IFAC), Chair of the CAA Committee for Women in Automation, and Chair of the Academic Committee on Automation of the Nonferrous Metals Society of China.

Prof.Yongduan Song

IEEE/ AAIA/ CAA Fellow

Chongqing University, China

Yongduan Song, a Doctoral Supervisor and Fellow of IEEE, AAIA, and CAA, is an Academician of the International Eurasian Academy of Sciences, a Registered Professional Engineer (USA), and an honoree in Who's Who Among America's Teachers. He serves as an Executive Council Member of the Chinese Association of Automation. Currently, he holds the positions of Director of the Artificial Intelligence Research Institute at Chongqing University, Editor-in-Chief of IEEE Transactions on Neural Networks and Learning Systems, and Head of the Smart Engineering Research Institute at Chongqing University. He obtained his Ph.D. in Electrical and Computer Engineering from Tennessee Technological University, USA, in 1992. His accolades include four first-place awards and two second-place awards from the Ministry of Education of China, Chongqing Municipality, Chinese Association of Automation, and Chinese Institute of Command and Control. Professor Song's research encompasses intelligent control, fault-tolerant control, adaptive coordinated control, aircraft navigation and control, renewable energy systems, robotics and intelligent unmanned systems, collective intelligence systems, biomimetic intelligent control systems, coordinated control theory and applications, and active safety early warning and control for complex systems.

Prof.Peng Zeng

Member of European Academy of Sciences and Arts

Shenyang Institute of Automation (SIA), Chinese Academy of Sciences, China

Peng Zeng, Ph.D. Supervisor at the Shenyang Institute of Automation (SIA), Chinese Academy of Sciences, received his Bachelor of Engineering degree from the Department of Computer Science at Shandong University in 1998 and his Ph.D. in Mechatronic Engineering from SIA in 2005. After completing his doctorate, he continued working at the institute, being appointed as a Research Professor in 2007. He served as Director of the Industrial Control Networks and Systems Laboratory from 2013, became Assistant Director of the institute in 2018, and was appointed Deputy Director in 2022. Professor Zeng holds key academic roles including Chair of the Technical Committee on Edge Computing of the Chinese Association of Automation (CAA), Vice Chair of the CAA Technical Committee on Control and Decision for Cyber-Physical Systems, Expert on the National Key R&D Program Major Project Expert Group for Smart Grid in the Energy Sector, Vice Chair of the CAA Technical Committee on Automation Instrumentation and Apparatus, and serves as an expert for both the IFAC Technical Committee on Networked Systems and the IEC Technical Committee on Industrial Measurement and Control. His research focuses on two primary domains: 1) Wireless Sensor Networks, encompassing the design and development of intelligent sensor nodes with sensing, computing, and communication capabilities; research on wireless ad-hoc networking methods (including wireless access, routing, transport control, and autonomous management); distributed information processing methods; and large-scale wireless sensor network system design and development; and 2) Industrial Wireless Communications, involving research on interference resistance, real-time communication, energy efficiency, and security technologies for wireless networks in complex industrial environments, along with the design and development of industrial wireless communication systems.

Prof. Jiye Liang

IEEE Fellow

Shanxi University, China

Liang Jiye, Ph.D., IEEE Fellow, Fellow of the China Computer Federation (CCF), and Fellow of the Chinese Association for Artificial Intelligence (CAAI), is a Professor and Doctoral Supervisor. He currently serves as the Director of the Academic Committee of Shanxi University and the Director of the Key Laboratory of Computational Intelligence and Chinese Information Processing (Ministry of Education) at Shanxi University. His previous leadership roles include serving as Executive Vice President of Shanxi University (at the university's highest administrative level) and President of Taiyuan Normal University. Professor Liang holds several significant national and academic appointments, including membership on the Special Committee on Artificial Intelligence, Blockchain, and Science & Technology Ethics under the Ministry of Education's Science and Technology Commission, membership on the Ministry of Education's Teaching Guidance Committee for Computer Science and Technology, Council Member of the CCF, Executive Council Member of the CAAI, Chair of the CCF Technical Committee on Artificial Intelligence and Pattern Recognition, and Chairman of the Shanxi Computer Society. He is also recognized as an Expert Receiving Special Government Allowances from the State Council.

Professor Liang's primary research and teaching focus on Artificial Intelligence, Machine Learning, and Big Data Analytics & Mining. In recent years, he has led numerous major national research initiatives, including one National Sci-Tech Innovation 2030 - "New Generation Artificial Intelligence" Major Project, four Key Projects under the National Natural Science Foundation of China (NSFC) / Joint Funds, two National High-Tech R&D Program (863 Program) Projects, and six NSFC General Program Projects. His extensive publication record comprises over 400 papers in prominent international and domestic academic journals and conferences, such as AI, JMLR (Journal of Machine Learning Research), IEEE TPAMI (IEEE Transactions on Pattern Analysis and Machine Intelligence), IEEE TKDE (IEEE Transactions on Knowledge and Data Engineering), ML (Machine Learning), NeurIPS (Conference on Neural Information Processing Systems), ICML (International Conference on Machine Learning), CVPR (IEEE/CVF Conference on Computer Vision and Pattern Recognition), and AAAI (AAAI Conference on Artificial Intelligence), with over 300 papers indexed by SCI.