 | Prof. Xiaofei ZhuChongqing University of Technology Xiaofei Zhu is a full Professor and Associate Dean of the School of Computer Science and Engineering at Chongqing University of Technology. He has been recognized as a National Outstanding Talent in Cyberspace Affairs, an Academic and Technical Leader of Chongqing, an Innovation Leading Talent under the Chongqing Talents Program, and a member of Chongqing’s “Hundred Overseas High-Level Talents” Program. His research focuses on big data analytics, artificial intelligence, recommender systems, and information security. He has published over 60 papers in venues including TKDE, KDD, WWW, and SIGIR. His honors include the ACM CIKM Best Paper Award and first place in the CIKM AnalytiCup. He served as Program Committee Chair of CCIR and Area Chair of CIKM. Title：Granular-Ball Computing for Recommender Systems: A New Perspective to Adaptive Preference Modeling |
 | Prof. Yazhou RenUniversity of Electronic Science and Technology of China Yazhou Ren is a Professor and PhD Supervisor at the School of Computer Science and Engineering, University of Electronic Science and Technology of China (UESTC). He is a Senior Member of IEEE, CCF, and CSIG, a recipient of the 2023 UESTC “Academic Rising Star” Award, and has been named to the World's Top 2% Scientists list (2024, 2025). His research focuses on multi-view learning, computer vision, and intelligent healthcare. As first or corresponding author, he has published over 90 papers in leading conferences such as ICML, NeurIPS, AAAI, CVPR, and ICCV, as well as in top journals including TPAMI, TMM, TKDE, TNNLS, and TGRS, with a total of more than 140 publications, comprising 1 ESI hot paper, 5 ESI highly cited papers, and 1 best paper award at an international conference. His work has accumulated over 7,000 Google Scholar citations. He has led more than 20 national-, and provincial-level research projects as well as industry-academia-research collaborations, and his algorithms have been deployed in real-world applications including industrial quality inspection, smart cultural tourism, and intelligent healthcare. Title：Granular-Ball Computing: Frontier Exploration from Computer Vision to Multi-View Clustering |
 | Prof. Dongdong ChengYangtze Normal University Dongdong Cheng, a professor, is a and a young scholar of Bayu Scholar. She is a reserve candidate for the Chongqing Academic and Technical Leaders Program, an inductee of the Chongqing Postdoctoral Innovation Talent Support Program, and the head of the Chongqing Women's Science and Technology Innovation Team. In recent years, she has mainly focused on researching clustering issues related to large-scale complex data. She has published over 30 papers in top academic journals and conferences such as IEEE TKDE, TNNLS, TSMC-S, and ICDE, and has authored one academic monograph. She has led and participated in multiple national natural science projects, as well as six provincial and ministerial-level projects. As the first contributor, she won the third prize of the Chongqing Natural Science Award. She serves as a council member of the Chongqing Computer Society and a reviewer for journals such as IEEE TPAMI, TKDE, and TNNLS. Title：Granular Ball-Based Clustering for Large-Scale Data with Complex Distributions |
 | Prof. Jie YangZunyi Normal University, China Jie Yang, born in 1987, holds a Ph.D. and is currently a Professor in the Department of Electronics at Zunyi Normal University and a Master's supervisor at Chongqing University of Posts and Telecommunications. She is the leader of the Multi-granularity Intelligent Computing Innovation Team of Higher Education Institutions in Guizhou Province, and has been selected for the Guizhou Outstanding Young Scientific and Technological Talents program and the Guizhou Top Scientific and Technological Talents program. She has published more than 40 papers in prestigious academic journals at home and abroad, including IEEE TNNLS, IEEE TFS, IEEE TETCI, IEEE TCBB, IEEE TKDE, and the Chinese Journal of Computers. She has published one monograph with Science Press. She has presided over two projects funded by the National Natural Science Foundation of China. She was awarded the Outstanding Doctoral Dissertation of Chongqing Municipality and the Third Prize of the Guizhou Provincial Science and Technology Progress Award Title:A Cloud-Model-Guided Shadowed Granular Ball Classifier |
 | Prof. Chao ZhangShanxi University, China Chao Zhang is a Professor and Ph.D. Supervisor at the Institute of Intelligent Information Processing, Shanxi University. His research interests include data mining, time-series analysis, and intelligent decision-making. He has led three projects funded by the National Natural Science Foundation of China, as well as more than ten national, provincial, and regional research projects. He has published over 100 papers in leading venues, including WWW, IJCAI, CIKM, IEEE TKDE, IEEE TNNLS, and IEEE TCYB. He has also authored two monographs and holds multiple invention patents. His honors include the 2024 Shanxi Provincial Science and Technology Award in Natural Science, as the third contributor, and the Second Prize of the 11th Shanxi Provincial Outstanding Social Science Research Achievement Award. He has been recognized as a Young Top Talent in Science and Technology Innovation in Shanxi Province and has been repeatedly listed among the world’s top 2% scientists. He serves as an Executive Member of the Granular Computing and Knowledge Discovery Committee and a Member of the Artificial Intelligence Foundations Committee of the Chinese Association for Artificial Intelligence. He also serves as an Editorial Board Member of Information Processing & Management and an Associate Editor of Computational Intelligence. His students have received first prizes in major academic competitions, including the Challenge Cup and the China College Students Service Outsourcing Innovation and Entrepreneurship Competition. Title: Granular-Ball Representations for Traffic Flow Forecasting |
 | Assoc. Prof. Suzhen YuanChongqing University of Posts and Telecommunications Dr. Suzhen Yuan is an associate Professor and Ph.D. supervisor at Chongqing University of Posts and Telecommunications (CQUPT), selected into CQUPT's "Wenfeng Young Hundred Talents Program." She received her Ph.D. in Engineering from Beihang University in 2015 and has conducted visiting research at the University of Otago (New Zealand), Tecnológico de Monterrey (Mexico), Nanyang Technological University (Singapore), and the University of Electronic Science and Technology of China. She has long been engaged in research on quantum machine learning, granular-ball computing, computer vision, and deep learning, with a focus on multi-granularity knowledge modeling, quantum feature mapping, and quantum kernel methods and their applications in intelligent perception tasks. She has led multiple projects including the National Natural Science Foundation of China, published over 30 SCI-indexed papers, and filed more than 10 patent applications. Title: Granular-Ball Quantum Clustering for Resource-Efficient and Robust Learning |
 | Assoc. Prof. Lifeng ShenChongqing University of Posts and Telecommunications Chao Zhang is a Professor and Ph.D. Supervisor at the Institute of Intelligent Information Processing, Shanxi University. His research interests include data mining, time-series analysis, and intelligent decision-making. He has led three projects funded by the National Natural Science Foundation of China, as well as more than ten national, provincial, and regional research projects. He has published over 100 papers in leading venues, including WWW, IJCAI, CIKM, IEEE TKDE, IEEE TNNLS, and IEEE TCYB. He has also authored two monographs and holds multiple invention patents. His honors include the 2024 Shanxi Provincial Science and Technology Award in Natural Science, as the third contributor, and the Second Prize of the 11th Shanxi Provincial Outstanding Social Science Research Achievement Award. He has been recognized as a Young Top Talent in Science and Technology Innovation in Shanxi Province and has been repeatedly listed among the world’s top 2% scientists. He serves as an Executive Member of the Granular Computing and Knowledge Discovery Committee and a Member of the Artificial Intelligence Foundations Committee of the Chinese Association for Artificial Intelligence. He also serves as an Editorial Board Member of Information Processing & Management and an Associate Editor of Computational Intelligence. His students have received first prizes in major academic competitions, including the Challenge Cup and the China College Students Service Outsourcing Innovation and Entrepreneurship Competition. Title: Granular-Ball Representations for Traffic Flow Forecasting |
 | Assoc. Prof. Binbin Sang Chongqing Normal University Binbin Sang, Ph.D., Associate Professor, Supervisor of Master’s Students, Assistant Dean, Young Talent under the Young Talent Support Program of the Chongqing Association for Science and Technology, and Young Top-notch Talent of the “Bowang Scholar” Program at Chongqing Normal University. He serves as an Editorial Board Member of Journal of Intelligent Systems (SCI) and a Guest Editor of Entropy (SCI) and Computers, Materials & Continua (SCI). He has presided two National Natural Science Foundation of China (NSFC) projects; he respectively presided the Chongqing Municipal Education Commission Science and Technology Major, Key, and Youth Projects; he presided over the Chongqing Natural Science Foundation General Project, etc.; and he mainly researched four NSFC projects. He has published more than fifty academic papers in high-level domestic and international journals such as IEEE TKDE, IEEE TFS, IEEE TSMC, IEEE TCYB, INF, and FSS. He received the Outstanding Paper Award at the 2026 Sichuan–Chongqing Science and Technology Academic Conference. He serves as a reviewer for multiple SCI (Top) journals, including IEEE TKDE, IEEE TFS, IEEE TNNLS, IEEE TCYB, IPM, KBS, and FSS. Title：Granular Ball Hypergraph Representation Learning and Knowledge Discovery Methods |
 | Assoc. Prof. Jiang XieChongqing University of Posts and Telecommunications Jiang Xie, born in 1988, is a Doctoral Supervisor, Associate Professor, and New Chongqing Youth Innovation Talent. He has extensive experience in both research and engineering practice in data mining and machine learning, and previously served as a Senior Algorithm Engineer at Huawei Technologies Co., Ltd. He has served as Principal Investigator for a National Natural Science Foundation of China project and a Chongqing Natural Science Foundation General Program project, and has participated as a core member in several National Key R&D Program projects. He has published more than ten high-quality academic papers in top-tier journals and conferences such as TPAMI, TKDE, TNNLS, and ICDE. Title：Research on the Theory and Methods of Granular Ball Computing for Unsupervised Data |
 | Assoc. Prof. Shu Dong HuangSichuan University Shu-Dong Huang, Associate Professor/Doctoral Supervisor at the School of Artificial Intelligence, Sichuan University. His main research focuses on multimodal representation learning, multimodal large models, etc. His has been funded by the National Natural Science Foundation of China, key research and development projects in Sichuan Province, general projects of natural sciences in Sichuan Province, and so on; He has published nearly 100 papers in Nature Communications, CCF A-class journals/conferences, with multiple are ESI highly cited papers; He has served as the Area Chair/Senior PC for academic conference such as ICLR, CVPR, ICML, NeurIPS, ICCV, AAAI, ACM MM, IJCAI, etc. He has been selected as one of the World's Top 2% Scientists ranked by Stanford University&Elsevier. He has won the first prize of Sichuan Provincial Natural Science Award in 2025 (4/5). Title：Multimodal Granular-ball Learning: Representation, Alignment, and Cross-Modal Retrieval |
 | Assoc. Prof. Doudou GuoChina University of Mining and Technology Doudou Guo is an associate professor at the School of Mathematics, China University of Mining and Technology. His research is focused on concept learning, cognitive computing, granular computing, and information fusion. He has published over 20 papers on these topics in the Journal of Information Fusion, Information Sciences, IEEE Transactions on Fuzzy Systems, IEEE Transactions on Neural Networks and Learning Systems, etc. Among them, 5 papers were selected as ESI highly cited paper, and 1 paper was selected as ESI hot cited paper. He has published 1 academic work with the Science Press. He is currently presiding over a National Natural Science Foundation project. He is currently a reviewer of IEEE TKDE, IEEE TSMC, IEEE TFS, IEEE TNNLS, IEEE TETCI, IEEE TAI, INF, INS, EAAI, PR, AIR, KIS, COGN, SOCO, IJMLC, NEPL, IJFS, etc. Title：Granular-Ball Concept-Cognitive Learning |
 | Asst. Prof. Zhongxiang DaiThe Chinese University of Hong Kong, Shenzhen Dr. Zhongxiang Dai is an Assistant Professor and Ph.D. Supervisor at the School of Data Science, The Chinese University of Hong Kong, Shenzhen. He has been selected for a national high-level young talent program and recognized as a Young Top Talent under Guangdong Province’s Pearl River Talent Plan. He has also been named a Presidential Young Fellow. He serves as Principal Investigator on projects supported by the Guangdong Provincial Natural Science Foundation’s Excellent Young Scientists Fund, the National Natural Science Foundation of China’s Young Scientists Fund (Category C), and the Shenzhen Natural Science Foundation’s General Program. Dr. Dai was a Postdoctoral Fellow at the Massachusetts Institute of Technology in 2024 and at the National University of Singapore from 2021 to 2023. He received his B.Eng. in Electrical Engineering in 2015 and his Ph.D. in Computer Science in 2021, both from the National University of Singapore. His research spans the theory and applications of machine learning. His applied research focuses on large language models (LLMs), including LLM-based agents, LLM-based social simulation, and the optimization of agent harnesses and skills. His theoretical research centers on multi-armed bandit algorithms. He has published more than 50 papers in leading AI conferences and journals, including 37 at NeurIPS, ICML, and ICLR. He serves as an Area Chair for NeurIPS, ICML, and ICLR, and as a Senior Program Committee (SPC) member for AAAI. Title：Granular-Ball Computing and Agents: Exploring Intersections and New Frontiers |
 | Assoc. Prof. Zhong YuanSichuan University Zhong Yuan is currently an Associate Professor at the School of Artificial Intelligence, Sichuan University. His research interests mainly focus on uncertainty artificial intelligence, uncertainty modeling, granular computing, self-supervised learning and anomaly detection. He received his Ph.D. degree in Computer Science and Technology from Southwest Jiaotong University in 2022. He has published more than 100 papers in prestigious journals and conferences, including IEEE TKDE, IEEE TFS, IEEE TSMCA, IEEE TCYB, IEEE TNNLS, etc. Among them, 3 papers have been recognized as ESI Highly Cited Papers. He serves as an Associate Editor of Pattern Recognition, Expert Systems and Scientific Reports, and Guest Editor of a special issue in Entropy. He also regularly acts as a reviewer for a number of top international journals, including IEEE TPAMI, IEEE TKDE, IEEE TFS, IEEE TSMCA, IEEE TCYB, IEEE TNNLS, etc. Title：Granular-Ball Anomaly Detection: Foundations, Methods and Frontiers |
 | Lecturer Zeli WangChongqing University of Posts and Telecommunications Zeli Wang received her Ph.D. degree from Huazhong University of Science and Technology (HUST), China, in 2022. She is currently a Lecturer with the College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, China. Her research interests include AI security and robustness, granular-ball computing, multi-granularity learning, graph machine learning, and smart contract security. Her recent research focuses on robust intelligence under noisy and adversarial environments, particularly exploring granular-ball computing and multi-granularity representations for textual adversarial attack and defense, noise-robust learning, graph data analysis, and smart contract vulnerability detection. . Her research has been published in international journals and conferences including KDD, WWW, TKDE, ICMR, TBD, etc. Title：Granular-Ball Computing for Robust Intelligence: From Multi-Granularity Representation to Adversarial Learning and Security Detection |