Invited Speaker Ⅰ

 Assoc. Prof. Mengyang Zhang

Shandong Normal University, China

Brief Introduction: Dr. Mengyang Zhang is an Associate Professor and Master’s Supervisor at the School of Information Science and Engineering, Shandong Normal University. He earned his Ph.D. in Control Science and Engineering from Shandong University in 2019 and has since dedicated his research to knowledge representation, intelligent perception and modeling, and task planning for domestic robots. He has authored over 40 publications in leading journals such as IEEE Transactions on Cybernetics, IEEE Transactions on Multimedia, IEEE Transactions on Industrial Electronics (TIE), along with over 10 authorized national invention patents. Dr. Zhang has led four major research projects, such as the National Natural Science Foundation of China (Youth Program) and the Shandong Natural Science Foundation (Youth Program), and actively serves as Deputy Secretary-General of the Intelligent Robotics Committee at the Shandong Association of Automation. He is also a long-term reviewer for prestigious journals including IEEE Transactions on Cybernetics, IEEE Transactions on Multimedia, and Knowledge-based Systems, underscoring his academic leadership and expertise.

Speech Title: Research on Key Technologies of Adaptive Task Planning for Household Robots

Invited Speaker Ⅱ

 Prof. Ke Chen

Zhengzhou University, China

Brief Introduction: Chen Ke is a professor and master's degree supervisor at Zhengzhou University. He has long been engaged in the research of complex data information mining, swarm intelligence optimization theory, and intelligent fault diagnosis, achieving a series of innovative results. In recent years, he has published more than 30 papers in high-level academic journals and conferences such as IEEE TEVC, IEEE TCYB, and IEEE TSMC, of which four have been selected as ESI highly cited papers. He has applied for 13 invention patents, six of which have been authorized. He currently serves as a member of the Young Committee of the Chinese Association for Artificial Intelligence, an expert reviewer for the Ministry of Education's degree theses, and an expert reviewer for Henan Province's science and technology projects. He also acts as a guest reviewer for more than 20 high-level journals/conferences, including IEEE TEVC, IEEE TCYB, IEEE TSMC, and IEEE TAI. He has been selected as a high-level talent in Henan Province, a distinguished young talent in Zhongyuan, and a young talent supported by the Henan Provincial Association for Science and Technology. He has presided over six national/provincial-level projects, including the National Natural Science Foundation of China for Young Scientists and the Special Financial Grant from the China Postdoctoral Science Foundation. He has won two first prizes for scientific and technological academic papers from the Henan Provincial Department of Education, a nomination for the Outstanding Doctoral Dissertation Award from the Chinese Association of Automation, and the Best Creative Idea Award at the Henan Province Postdoctoral Innovation and Entrepreneurship Competition.

Speech Title: Research on Feature Selection Method for Complex Data Based on Evolutionary Computation and Its Applications

Abstract: With the rapid advancement of information technology, the collected data exhibit composite characteristics such as discretization, high dimensionality, strong sparsity, and multi-objectivity. As a result, the information extraction methods based on traditional data analysis techniques can no longer effectively meet the practical application requirements. Feature selection, as an effective data preprocessing technique, can directly select useful features from the original feature space to construct learning models and achieve superior generalization performance compared to the original feature set. It has become a research hotspot in the field of data mining and has been widely applied in text mining, key gene detection, image processing, and other fields. This report will revolve around the issue of acquiring key features of data, integrating evolutionary computation methods, and starting from the perspectives of problem characteristic mining and knowledge transfer, to focus on the design of feature selection methods and their application in the fault diagnosis of rotating machinery.

Invited Speaker Ⅲ

Assoc. Prof. Xiao Liang

Nankai University, China

Brief Introduction: Xiao Liang is currently an Associate Professor at College of Artificial Intelligence, Nankai University. He received his Ph.D. in Control Science and Engineering from at Nankai University in 2018. His research primarily focuses on intelligent control and perception for unmanned systems. Dr. Liang was selected for the Tianjin Young Talent Support Program and won the First Prize in the Tianjin Intellectual Property Innovation & Entrepreneurship Invention and Design Competition. He has led multiple research projects, including: National Natural Science Foundation of China (NSFC) General & Youth Programs, Sub-task of National Key R & D Programs. He has published over 20 academic papers in journals including IEEE Transactions.

Speech Title: Research on Key Technologies for Aerial Transportation and Manipulation by Multirotors

Abstract: While unmanned aerial vehicles (UAVs) are mainly used for non-contact observation (e.g., monitoring, photography, reconnaissance), multirotors also excel in operational tasks including aerial cable-suspended transportation and manipulation. The aerial transportation system utilizes a sling to connect the load to the multirotor, effectively leveraging the high maneuverability of the multirotor. By installing a multi-link manipulator arm at the bottom of the multirotor, the aerial manipulation system can directly perform active operations on the load, allowing for more complex interactive tasks. These capabilities significantly expand UAV functionality beyond passive observation, allowing active engagement with environments and targets.

Invited Speaker Ⅳ

Assoc. Prof. Jiyu Cheng

Shandong University, China

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.