Associate Professor in the State Key Laboratory of AI Safety, Institute of Computing Technology, Chinese Academy of Sciences (ICT, CAS). He received Ph.D. degree in Computer Science from the Institute of Computing Technology, CAS in 2015 and B.S. degree in Computer Science from Zhejiang University in 2010. His research interests include algorithms and models for AI finance tasks, e.g. graph learning for financial applications and NLP for financial applications. His work on graph-based fraud detection was honored with the Best Short Paper Honorable Mention at CIKM 2022, and he was the first to pioneer the Event-Level Financial Sentiment Analysis (EFSA) task. He has authored more than 100 referred publications at prestigious international conferences and journals like The Innovation, IEEE TKDE, KDD, WWW, SIGIR, ACL, ICLR etc., and has served as SPC or PC members over top tier international conferences such as KDD, WWW, IJCAI, AAAI, ACL, NeurIPS, ICML, etc. 

Assistant Professor in the State Key Laboratory of AI Safety, Institute of Computing Technology, Chinese Academy of Sciences (ICT, CAS). He got his PhD from Institute of Computing Technology Chinese Academy of Sciences in 2023. From Feb 2022 to Feb 2023, he was a visiting scholar in the NExT Research Centre, National University of Singapore(NUS). Previously, he received the B.S. degree in Mathematics from Nanjing University in 2017. His research interests include Financial Data Mining and Trustworthy Graph Machine Learning, among others. He has published over 20 referred papers on graph-based financial data mining at prestigious international conferences and journals including The Innovation, IEEE TKDE, KDD, WWW, ICLR, etc., and has served as PC members over top tier international conferences such as KDD, WWW, IJCAI, AAAI, NeurIPS, ICML, etc.  

Dr. Guansong Pang is a tenure-track Assistant Professor of Computer Science and Lee Kong Chian Fellow at the School of Computing and Information Systems, Singapore Management University (SMU), where he leads the Machine Learning & Applications(MaLA) Lab. He is also a faculty member of Centre on Security, Mobile Applications and Cryptography. His research interests include machine learning, data mining, and computer vision, with a research theme focused on recognizing and generalizing to abnormal/unknown/unseen data for creating trustworthy AI systems. His research has attracted 10,000+ citations and received multiple global recognition/awards, e.g., the prestigious 2020 UTS Chancellor’s Award List, the World’s Top 2% Scientists in 2022-2024, DSAA 2023 Best Paper Award, and Most Influential KDD 2023 Paper. He actively engages in various professional activities, serving as Area Chair or Senior PC Member of NeurIPS, ICLR, ICML, CVPR, KDD, PAKDD, IJCAI, and AAAI, Associate Editor of IEEE TNNLS and Pattern Recognition, and Editorial Board member of IEEE Intelligent Systems and International Journal of Data Science and Analytics.  

Ph.D. candidate at the State Key Laboratory of AI Safety, Institute of Computing Technology, Chinese Academy of Sciences (ICT, CAS), under the supervision of Prof. Xiang Ao. He received B.S. degree in Computer Science and Technology from University of Chinese Academy of Sciences in 2023. His research interests broadly encompass Safety and Security of Machine Learning, with a particular focus on Graph Adversarial Learning.  

Ph.D. candidate at Singapore Management University. His research interests include graph representation learning, graph anomaly detection, and the combination of anomaly detection and large language models. He has published multiple articles in refereed top-tier venues, including NeurIPS, ICML, KDD, IJCAI, and TKDE. He has received several awards, such as the Mark Weiser Best Paper Award in PerCom (2024) and SMU Presidential Doctoral Fellowship Award (2024,2025), SMU Dean List (2025) and President’s Award of the Chinese Academy of Sciences (2022), First prize, Dean Scholarship of Chengdu Branch, Chinese Academy of Science (2021). He also served on the program committees of multiple top conferences and journals.  

Dr. Dawei Cheng is currently an Associate Professor appointed at the School of Computer Science and Technology of Tongji University, Shanghai, China. He serves as dean assistant of Collaborative Innovation Center of Internet Finance Safety, and guest Ph.D. supervisor at the University of Technology Sydney, Australia. He specializes in data mining, machine learning, deep learning and reinforcement learning. Now he mainly focuses on graph learning, big data in finance, deep learning in complex graphs, generative artificial intelligence and large-scale graph analysis.  

Dr. Qing He is a Full Professor at the Institute of Computing Technology, Chinese Academy of Sciences(CAS), and he is a Professor of University of Chinese Academy of Sciences (UCAS). He is also the Vice Secretary of Chinese Association for Artificial Intelligence, the Member of China Computer Federation Artificial Intelligence and Pattern Recognition Committee, the Member of Chinese Institute of Electronics and Clouding Computing and Big Data Experts Committee. His interests include data mining, machine learning, classification, fuzzy clustering, cloud computing, and big data. A series of achievements have been gained in fuzzy information processing, fuzzy clustering, knowledge representation, text information processing, and big data mining based on cloud computing. More than 100 papers have been published in journals, 40 of which are SCI Indexed, 66 of which are EI Indexed.