Speakers 2025

Keynote Speaker Ⅰ

Prof. Huiyu Zhou

University of Leicester, United Kingdom

Brief Introduction: 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. Prof. Zhou currently is a full Professor at School of Computing and Mathematical Sciences, University of Leicester, United Kingdom. He has published over 550 peer-reviewed papers in the field. He was the recipient of "CVIU 2012 Most Cited Paper Award", “MIUA 2020 Best Paper Award”, “ICPRAM 2016 Best Paper Award” and was nominated for “ICPRAM 2017 Best Student Paper Award” and "MBEC 2006 Nightingale Prize". Prof. Zhou serves as the Editor-in-Chief of Recent Advances in Electrical & Electronic Engineering and Associate Editor of IEEE Transaction on Human-Machine Systems, IEEE Journal of Biomedical and Health Informatics, Pattern Recognition, Scientific Reports, Security and Safety, Machine Intelligence Research, PeerJ Computer Science and IEEE Access, and Area Chair of ICRA, IJCAI and BMVC. He is one of the Technical Committee of “IEEE Cognitive and Development Systems”, “Information Assurance & Intelligent Multimedia-Mobile Communication in IEEE SMC Society”, “Robotics Task Force” and “Biometrics Task Force” of the Intelligent Systems Applications Technical Committee, IEEE Computational Intelligence Society. He has given over 150 invited talks at international conferences, industry and universities, and has served as a chair for 100 international conferences and workshops. His research work has been or is being supported by UK EPSRC, MRC, EU, Royal Society, Leverhulme Trust, Puffin Trust, Alzheimer’s Research UK, Invest NI and industry. Homepage: https://le.ac.uk/people/huiyu-zhou

Speech Title: Artificial intelligence in telecommunication – Past, Present and Future

Abstract: Artificial intelligence (AI) has been pervasive in many areas of recent scientific and technological development since 2010. Recent research progresses and wide applications include ChatGPT, Claude and Sora, which significantly demonstrate the power of generative artificial intelligence and other AI tools. However, it is not clear how to utilise the available AI technologies for improving quality of various services and products. In this talk, we will start from an example of using ChatGPT to explore the capabilities of AI in telecommunication research. We will discuss how AI helps and supports the development of 5G/6G systems in recent years. Afterwards, we discuss several well-recognised AI systems available to use online, before we explore the missing aspects in those AI systems/tools. Finally, we elaborate the needs of collaboration over different countries. 

Keynote Speaker Ⅱ

Prof. Lei Zhang

Northwestern Polytechnical University, China

Brief Introduction: Prof. Lei Zhang received his bachelor's and doctoral degrees from the School of Computer Science, Northwestern Polytechnical University in 2012 and 2018, respectively. He is mainly engaged in teaching and research in the fields of image processing and machine learning. In recent years, he has published more than 90 papers in top journals and conferences in the field of computer vision, such as IJCV, IEEE TIP, IEEE TGRS, IEEE TNNLS, IEEE TCSVT, IEEE TCI, CVPR, ICCV, AAAI, ECCV, ICME, etc.

Keynote Speaker Ⅲ

Prof. Tao Zhou

North Minzu University, China

Brief Introduction: Tao Zhou is currently a professor in School of Computer Science and Engineering, North Minzu University, Yinchuan, China. He is also a Ph.D. Supervisor in Institute for Medical Informatics, University of Huaqiao, Fuzhou, China. He obtained his PhD degree from Computer Science and technology, Northwestern Poly-technology Univ. in China. he has been a visiting scholar in The University of Leicester, UK. Chinese University of Hong Kong, HK, ShanDong University, China. His research interests include pattern recognition, machine learning, machine vision, medical image analysis. He has published over 220 academic papers in top journal or conference, such as Information Fusion, Applied Soft Computing, CIBM, CMPB, BSPC, Acta Electronica Sinica, et. al., 3 ESI Papers. he has published 3 books, Furthermore, he has obtained 6 authorized patents. He served for the NCIG2020,ICIG2021,ICIGP 2022 & IFSP2022，ICDIP2022 as Technical Co-Chair or Publicity Co-Chair.

Invited Speaker Ⅰ

Prof. Wei Song

Jiangnan University, China

Brief Introduction: Wei Song is a Professor and PhD Supervisor at Jiangnan University, IEEE Senior Member, IEEE CIS/SMCS Senior Member, and Vice Dean of the School of Artificial Intelligence and Computer Science. He has published over 100 papers in conferences and journals such as IEEE TNNLS, TEVC, TCYB, TSMC-S, TETCI, etc., and holds 12 authorized invention patents. His has achieved two First Prizes and one Second Prize in the Science and Technology Award from the China General Chamber of Commerce, the Rong Zhiquan Award, and the Sangma Award. He has served as a conference/communication reviewer for the National Natural Science Foundation of China (NSFC), the Ministry of Education Degree Center, and as a program committee member for several international conferences.

Speech Title: Learning-driven Evolutionary Search for Solving Dynamic Multiobjective Optimization Problems

Abstract: In dynamic optimization problems, environmental changes can be characterized as various dynamics and pose a challenge to dynamic optimization algorithms. However, existing swarm intelligence-based dynamic optimization algorithms mainly rely on some predetermined rules, limiting their capability in handling various dynamics. Additionally, diversity loss remains a critical issue behind the inefficiency of existing dynamic optimization algorithms. Consequently, maintaining high diversity in dynamic environments is essential for automatically addressing this challenge. Faced with these challenges, a series of neural network-assisted dynamic optimization algorithms are proposed. For dynamic optimization problems, we design a particle search control network to automatically determine the learning targets and accelerating coeffect for each individual in the population; For multi-objective optimization problems under diverse dynamics, we design a dynamic optimization algorithm based on a swarm behavior decision neural network and an efficient hidden node adjustment mechanism. These algorithms are capable of solving dynamic optimization and dynamic multi-objective optimization problems across various dynamics with very small time cost.

Invited Speaker Ⅱ

Assoc. Prof. Jiyu Cheng

Shandong University, China

Brief Introduction: Jiyu Cheng received the B.E. degree in automation from Shandong University, Jinan, China, in 2015 and the Ph.D. degree in department of electronic engineering from the Chinese University of Hong Kong, Hong Kong, in 2019. He is currently an Associate Research Professor with the Department of Control Science and Engineering, Shandong University. His current research interests include multirobot system, deep learning, and reinforcement learning.

Speech Title: Multirobot Autonomous Collaboration in Complex Scenarios

Abstract: Multirobot collaboration plays a vital role in many real-life applications, such as inspection, search and rescue and so on. As a main research branch in robotics, it has attracted wide attention and developed rapidly. However, efficient collaboration in especially large and unstructured environments is still a challenging problem. In this talk, we will introduce our recent research on several typical multirobot tasks and talk about our exploration on how the data driven approach can empower the collaboration in a multirobot system.

Invited Speaker Ⅲ

Prof. Xiaolin Qin

University of Chinese Academy of Sciences, China