分会1：Intelligent Systems and Its Applications

分会主席： Prof. Zne-Jung Lee Fuzhou University, China
Dean. Kaihui Li/Mingchuan University
Prof. Bojun Huang

Zne-Jung Lee received the Ph.D. degree in electrical engineering from National Taiwan University of Science and Technology (NTUST), Taipei, Taiwan, in 2002. He is a full professor with the School of Advanced Manufacturing, Fuzhou University, China. He published more than 240 papers in journal or conference including more than 80 papers in SCI/SSCI/EI. His current research interests include artificial intelligence, big data, data mining, and computational intelligence. He has been listed in the World’s Top 2% Scientists from 2020 to 2023.

分会2：Research Progress on the Integrity and Sharing of Cloud Storage Data

分会主席： Prof. Lunzhi Deng Guizhou Normal University, China

Lunzhi Deng received the B.S. and M.S. degrees in applied mathematics from Guizhou Normal University, Guiyang, PR China, in 2002 and 2008, respectively, and the Ph.D. degree in applied mathematics from Xiamen University, Xiamen, PR China, in 2012. He is now a professor in the School of Mathematical Sciences, Guizhou Normal University, Guiyang, PR China.

分会3: Interdisciplinary Insights into Spatio-Temporal Data Mining for Predictive Modeling in Nanomaterials Science

分会主席： Ph.D. Zhexu XI-Bristol Centre for Nanoscience and Quantum Information, University of Bristol

Through rigorous exploration and analysis, I delved into the intricate complexities inherent within nanomaterial systems, employing advanced computational methodologies to elucidate their underlying patterns and behaviors. This multifaceted approach involved the integration of cutting-edge techniques from the realms of data science, machine learning, and materials informatics, thereby facilitating the development of predictive frameworks capable of discerning intricate relationships within vast datasets. By leveraging insights derived from temporal and spatial dimensions, coupled with algorithmic sophistication, my endeavors aimed to contribute towards the advancement of predictive modeling techniques tailored specifically to the realm of nanomaterial research.