Applied mathematics and machine learning are converging at pace, giving rise to scientific machine learning and data-driven modelling across PDEs, inverse problems and control. This convergence is reshaping methods and applications in science and engineering.
Key current directions
· Physics-informed learning for PDEs and dynamical systems.
· Neural operators and fast surrogates for simulation.
· Data-driven modelling, inverse problems and imaging.
· Optimisation, control and “learning to optimise”.
· Explainable/trustworthy AI in high-stakes settings.
· Cross-disciplinary and industrial applications.
Scientific Committee
· Enrique Zuazua. FAU Erlangen-Nürnberg (Germany)
· Ran Zhang. Jilin University (China)
Organizing Committee
· Ran Zhang (Jilin University)
· Chunpeng Wang (Jilin University)
· Jiwei Jia (Jilin University)
· Ping Lin (Northeast Normal University)
· Xu Liu (Northeast Normal University)
· Yubiao Zhang (Jilin University)
· Kai Zhang (Jilin University)
· Yongyi Yu (Jilin University)
Plenary Speakers
· Zhiming Chen (Academy of Mathematics and Systems Science, Chinese Academy of Sciences)
· Arnulf Jentzen (CUHK-Shenzhen & University of Münster)
· Shi Jin (Shanghai Jiao Tong University)
· Zhen Lei (Fudan University)
· Marius Tucsnak (University of Bordeaux)
· Gengsheng Wang (Tianjin University)
· Bo Zhang (Academy of Mathematics and Systems Science, Chinese Academy of Sciences)
· Xu Zhang (Sichuan University)
· Jun Zou (The Chinese University of Hong Kong)
Speakers
· Ilias Ftouhi (Nîmes University)
· Guanghui Hu (Nankai University)
· Long Hu (Shandong University)
· Kang Liu (Université de Bourgogne)
· Nana Liu (Shanghai Jiao Tong University)
· Lorenzo Liverani (FAU Erlangen-Nürnberg)
· Qi Lv (Sichuan University)
· Yue Wang (Fudan University)
· Shengquan Xiang (Peking University)
· Can Zhang (Wuhan University)
· Yaoyu Zhang (Shanghai Jiao Tong University)
· Yubiao Zhang (Jilin University)
Conference Date September 17-September 19,2026
Conference Venue Zhengxin Building, Jilin University
