Distinguished Professor, Tongji University

Research interest: complex systems, AI for science

Biography: Gang Yan is currently a Distinguished Professor at the School of Physical Science and Engineering and the State Key Laboratory of Autonomous Intelligent Systems, Tongji University, Shanghai, China. He received his B.S. and Ph.D. degrees from the University of Science and Technology of China. Prior to joining Tongji University, he worked as a Research Scientist at Temasek Laboratories, National University of Singapore, and later as a Research Fellow at the Network Science Institute, Northeastern University, USA. His research interests lie at the intersection of complex systems and AI for Science (AI4S), focusing on developing innovative theories and computational tools to understand, anticipate, and control real-world complex networks and systems. His work has appeared in leading journals such as Nature, Nature Physics, Nature Computational Science, Nature Communications, Physical Review Letters, and Physical Review X, as well as top artificial intelligence conferences including NeurIPS, ICML, and AAAI.

Email: gyan AT tongji DOT edu DOT cn

Homepage: www.gangyanlab.com

Associate Professor (tenure-track), Tongji University

Research interest: network dynamics, self-organization and collective behaviour

Biography: Xiaozhu Zhang is currently an Associate Professor (tenure-track) at Tongji University, Shanghai, China. She obtained her B.Sc. in Optical Science and Engineering from Fudan University, before pursuing further studies in Germany, where she earned her B.Sc., M.Sc. (with Distinction), and Dr. rer. nat. in Physics at Georg-August-University Göttingen and the Max Planck Institute for Dynamics and Self-Organization. After over 13 years of research and training in Germany, she returned to her hometown Shanghai and joined Tongji University. Her research focuses on dynamics of complex networks, self-organization and collective behaviour, as well as nonlinear dynamical systems, especially perturbation spreading, pattern formation and risk assessment in networked systems. Her findings have been published in journals including Physical Review Letters, Science Advances, European Journal of Applied Mathematics and Chaos.

Email: xiaozhu_zhang AT tongji DOT edu DOT cn

Homepage: zhangxiaozhu.me/en/

Associate Professor (tenured), Tongji University

Research interest: Complex systems, statistical laws, complex networks, causal detection, network spreading

Biography: Jack Murdoch Moore is currently a Tenured Associate Professor at the School of Physical Science and Engineering, Tongji University, Shanghai, China. He earned his B.Sc. and Ph.D. degrees from the University of Western Australia. His research covers statistical physics, complex systems, network science, nonlinear time‑series analysis and causal detection. He works on network spreading, power‑law statistics, causal network reconstruction and critical‑transition related problems. His research outputs have been published in journals including Physical Review X, Physical Review Letters, Physical Review E, Communications Physics, as well as top AI conferences such as NeurIPS and AAAI.

Email: jackmoore AT tongji DOT edu DOT cn

Homepage: jackmurdochmoore.github.io/JackMurdochMoore/