Proceedings of the 3rd International Conference on Machine Learning, Cloud Computing and Intelligent Mining (MLCCIM2024): Volume 2 (Lecture Notes in Electrical Engineering, 1327)

The proceedings offer a meticulously curated compilation of peer-reviewed papers presented at the 3rd International Conference on Machine Learning, Cloud Computing and Intelligent Mining (MLCCIM2024). With a profound focus on these domains, this volume serves as an invaluable resource for researchers, experts, professionals, and practitioners engaged in machine learning, control systems, robot, cloud computing and intelligent mining techniques. The conference facilitated a vibrant exchange of knowledge, enabling participants to unveil their pioneering research findings, showcase the outcomes of their latest projects, and engage in thought-provoking discussions to share perspectives and experiences.

Fuchun Sun received the BS and MS degrees from Naval Aeronautical Engineering Academy, Yantai, China, in 1986 and 1989, respectively, and the PhD degree from Tsinghua University, Beijing, China, in 1998. From 1998 to 2000, he was a postdoctoral researcher with Department of Automation, Tsinghua University, where he is currently a professor with Department of Computer Science and Technology. His current research interests include intelligent control, neural networks, fuzzy systems, variable structure control, nonlinear systems, and robotics. He is a fellow of IEEE.

Hesheng Wang received the B.Eng. degree in Electrical Engineering from the Harbin Institute of Technology. Harbin, China, in 2002, the M.Phil. and Ph.D. degrees in Automation & Computer-Aided Engineering from the Chinese University of Hong Kong, Hong Kong, in 2004 and 2007, respectively. From 2007 to 2009, he was a Postdoctoral Fellow and Research Assistant in the Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong. He joined Shanghai Jiao Tong University as an Associate Professor in 2009. Currently, he is a Distinguished Professor of Department of Automation, Shanghai Jiao Tong University, China. He worked as a visiting professor at University of Zurich in Switzerland. His research interests include visual serving, service robot, robot control and computer vision.

Prof. Wang has published more than 200 papers in refereed professional journals and international conference proceedings. He has received a number of best paper awards from major international conferences in robotics and automation. Dr. Wang is an Associate Editor of IEEE Transactions on Automation Science and Engineering, IEEE Robotics and Automation Letters, Assembly Automation, IET Cyber-systems and Robotics, the International Journal of Humanoid Robotics, a Senior Editor of the IEEE/ASME Transactions on Mechatronics, an Editorial Advisory Board in Advanced Intelligent Systems. He served as an Associate Editor of the IEEE Transactions on Robotics from 2015 to 2019. He served as The Technical Activities Board Member of IEEE Robotics and Automation Society. He served an editor in Conference Editorial Board of IEEE Robotics and Automation Society since 2021. Prof. Wang is actively involving in organization of international conferences. He served as organizing committee member for many international conferences such as ICRA and IROS. He was the program chair of the 2014 IEEE International Conference on Robotics and Biomimetics, the program chair of the 2019 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, and the general chair of the 2016 IEEE International Conference on Real-time Computing and Robotics, the general chair of the 2022 IEEE International Conference on Robotics and Biomimetics. He will be the General Chair of The 2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS2025). He was a recipient of Shanghai Rising Star Award in 2014, The National Science Fund for Outstanding Young Scholars in 2017, Shanghai Shuguang Scholar in 2019 and The National Science Fund for Distinguished Young Scholars in 2022. He is a Senior Member of IEEE.

Han Long received the Ph.D. degree in construction engineering from Tongji University, Shanghai, China, in 2004. He was a postdoctoral researcher in applied mathematics. He was a visiting scholar at Warwick University. He has served as general chair/PC member of many international academic conferences such as ICONIP, MLCCIM, and ICCBDAI. He has been a director or a member in over 10 national grants and projects.

Yifei Wei received the B.Sc. and Ph.D. degrees in electronic engineering from the Beijing University of Posts and Telecommunications (BUPT), Beijing, China, in 2004 and 2009, respectively. He was a Visiting Ph.D. Student with Carleton University, Ottawa, ON, Canada, from 2008 to 2009. He was a Postdoctoral Research Fellow with Dublin City University, Dublin, Ireland, in 2013. He was the Vice Dean of School of Science, BUPT from 2014 to 2016. He was a Visiting Scholar with the University of Houston, Houston, TX, USA, from 2016 to 2017. He is currently a Professor and the Vice Dean of the School of Electronic Engineering with BUPT. His research interests include energy-efficient networking, heterogeneous resource management, machine learning, and edge computing. He is the Guest Editor for a special issue in IEEE Transactions on Green Communications and Networking in 2021. He also was a Symposium Co-Chair of IEEE Globecom 2020, and Track Co-Chair for International Conference on Artificial Intelligence and Security 2019, 2020, 2021 and 2022. He was the recipient of the Best Paper Awards at the ICCTA2011 and ICCCS2018. He has served on the Technical Program Committee members of numerous conferences.

Hongqi Yu received the B.S., M.S., and Ph.D. degrees from the National University of Defense Technology (NUDT), Changsha, China, in 2000, 2003, and 2007, respectively.,He is an Associate Professor at NUDT. He was an Academic Visitor at Center for Biophotonics, University of Strathclyde, Glasgow, U.K., from June 2014 to July 2015. His research interests focus around signal processing, SPAD based FLIM system and embedded system.