Speakers

Prof. Ying Tan
(Keynote Speaker)
Peking University, China

Keynote Lecture: Latest Progress of Fireworks Algorithm (FWA) & Its Applications

Abstract: Inspired from the collective behaviors of many swarm-based creatures in nature or social phenomena, swarm intelligence (SI) has been received attention and studied extensively, gradually becomes a class of efficiently intelligent optimization methods. Inspired by fireworks’ explosion in air, the so-called fireworks algorithm (FWA) was proposed in 2010. Since then, many improvements and beyond were proposed to increase the efficiency of FWA dramatically, furthermore, a variety of successful applications were reported to enrich the studies of FWA considerably. In this talk, the novel swarm intelligence algorithm, i.e., fireworks algorithm, is briefly introduced and reviewed, then several effective improved algorithms are highlighted, individually. In addition, the multi-objective fireworks algorithm and the graphic processing unit (GPU) based FWA are also briefly presented, particularly the GPU-based FWA is able to speed up the optimization process extremely. Extensive experiments on benchmark functions demonstrate that the improved algorithms significantly increase the accuracy of found solutions, yet decrease the running time sharply. Finally, several typical applications of FWA, in particular, for big-data application, are presented in detail.

Biography: Ying Tan is a full professor of Peking University, director of Computational Intelligence Laboratory at Peking University, and the inventor of Fireworks Algorithm (FWA). He worked as a professor of Faculty of Design, Kyushu University, Japan, in 2018, at Columbia University as senior research fellow in 2017, and at Chinese University of Hong Kong as research fellow, and at University of Science and Technology of China in 2005-2006 as a professor under the 100-talent program of CAS. He is the president of the IASEI, and also serves as the Editor-in-Chief of IASEI Transactions on Swarm Intelligence, and International Journal of Computational Intelligence and Pattern Recognition (IJCIPR), the Associate Editor of IEEE Transactions on Cybernetics (CYB), Neural Networks, International Journal of Swarm Intelligence Research (IJSIR), etc. He also served as an Editor of Springer’s Lecture Notes on Computer Science (LNCS) for 60+ volumes, and Guest Editors of several referred Journals, including IEEE/ACM Transactions on Computational Biology and Bioinformatics, Information Science, Neurocomputing, Natural Computing, Swarm and Evolutionary Optimization, etc. He is the founder general chair of the ICSI International Conference series since 2010 and the DMBD conference series since 2016. He won the 2nd-Class Natural Science Award of China in 2009 and 2nd-Class Natural Science Award of Ministry of Education of China in 2019 and many best paper awards. His research interests include computational intelligence, swarm intelligence, deep neural networks, machine learning, data mining, intelligent information processing for information security and financial prediction, etc. He has published 400+ papers in refereed journals and conferences in these areas, and authored/co-authored 18 books, including “Fireworks Algorithm” by Springer in 2015, and “GPU-based Parallel Implementation of Swarm Intelligence Algorithms” by Morgan Kaufmann (Elsevier) in 2016, and received 8 invention patents.

Prof. Leida Li
(Keynote Speaker)
Xidian University, China

Keynote Lecture: Fine-grained Visual Quality Assessment

Abstract: Visual quality assessment evaluates the perceptual quality of images by simulating the characteristics of the Human Visual System (HVS). As a common technology, it has important applications in many fields such as low-level vision, imaging optimization, smart photography, and AIGC. After more than 20 years of rapid development, a large number of algorithms have proposed. However, the existing methods typically suffer from insufficient discrimination ability when used in real-world environments. This keynote talk focuses on the key differences between coarse-grained and fine-grained visual quality assessment, the main research progress in fine-grained visual quality assessment in recent years, and future research directions.

Biography: Leida Li is a Full Professor at Xidian University, recognized as a National Young Talent. His research interests include computer vision, visual quality assessment, and computational aesthetics. He has published over 100 papers in top-tier journals and conferences like IEEE TPAMI, IEEE TIP, CVPR, ICCV, and AAAI, with more than 9600 Google citations. He has led five projects supported by the National Natural Science Foundation of China and has actively engaged in industry-academia collaborations with top companies such as Huawei, OPPO, and Tencent. He was awarded the "Outstanding Industry-Academia Collaboration Partner" by OPPO, and his research outcomes have been applied in OPPO ColorOS, live-streaming cameras. He is an Associate Editor of IEEE Transactions on Image Processing (TIP) and Journal of Visual Communication and Image Representation (Best Associate Editor Award 2021/2023), and serves as Area Chair/Senior Program Committee member for top international conferences such as AAAI, IJCAI, and ACM MM. He is a Senior Member of IEEE/CCF/CSIG.

Prof. Guangzhong Dong
(Keynote Speaker)
Harbin Institute of Technology, Shenzhen, China

Biography: Dr. Guangzhong Dong received his Bachelor of Science degree in Automation and his PhD in Software Engineering from the University of Science and Technology of China (USTC) in 2013 and 2018, respectively. After obtaining his PhD, he conducted postdoctoral research at City University of Hong Kong from July to December 2018, Chalmers University of Technology in Sweden from December 2018 to April 2020, and Nanyang Technological University in Singapore from November 2020 to October 2021. In October 2021, he joined the School of Mechanical Engineering and Automation at Harbin Institute of Technology (Shenzhen) as an Associate Professor in Control Science. He will become a Professor and Doctoral Supervisor at the School of Intelligent Science and Engineering, Harbin Institute of Technology (Shenzhen) in January 2025. His research focuses on battery energy storage system modeling, estimation, optimal control, fault reconfiguration, and health management. He has published over 40 academic papers in renowned SCI journals in the field of battery management and control, including over 20 as first author or corresponding author. He received the Special Doctoral Award from the Chinese Academy of Sciences in 2018. Thank you to all the students and colleagues who are interested in battery energy storage control and management technology for contacting and exchanging ideas.

Res. Haoran Li
(Keynote Speaker)
Institute of Automation, Chinese Academy of Sciences, China

Keynote Lecture: Reinforcement Learning-Based Post-Training of Vision-Language-Action Models

Abstract: In recent years, Vision-Language-Action (VLA) models have demonstrated remarkable potential for general-purpose robotic control. However, existing approaches still face significant challenges, including limited generalization in open-world scenarios, reduced robustness under dynamic disturbances, and insufficient precision in fine-grained manipulation tasks. Meanwhile, reinforcement learning (RL) has shown strong capabilities in robotic motion control and in the post-training of large language models. Integrating RL with VLA models—particularly through post-training—has emerged as a promising direction to address these limitations. In this talk, I will present recent progress on RL-based post-training for VLA models, focusing on policy modeling, reward design, and training framework development.

Biography: Haoran Li is an Associate Professor and Master’s Supervisor at the Institute of Automation, Chinese Academy of Sciences. His research focuses on deep reinforcement learning and its applications in embodied systems. He has published more than 40 papers in leading international journals, including IEEE TNNLS, IEEE TCYB, and IEEE TSMCS, as well as top-tier conferences such as NeurIPS, ICLR, CVPR, RSS, CoRL, ICRA. He has led and participated in several major research projects funded by the National Natural Science Foundation of China, including the Young Scientists Fund, key projects, and sub-projects of major programs. His teams have won five championships and three first prizes in national and international robotics competitions. He is also a recipient of the Second Prize of the Beijing Municipal Science and Technology Award.