From May 13 to 17, 2026, the China-Canada-Hungary Joint Workshop on Mathematics of Complexity in Public Health was successfully held at Fudan University, Shanghai. The workshop was jointly organized and supported by the Research Institute of Intelligent Complex Systems, Fudan University; School of Mathematical Sciences, Fudan University; Shanghai Center for Mathematical Sciences; Feishu, China; Fields Institute for Research in Mathematical Sciences, Canada; York University, Canada; Centre of Excellence in Artificial Intelligence for Public Health Advancement (AIPHA), Canada; National Laboratory for Health Security, Hungary; Hungarian National Laboratory; and the Bolyai Institute, University of Szeged, Hungary.

As the first workshop of the Canada-China-Hungary Network of Mathematics for Innovation in Public Health, or the C2H Network, the event marked an important step toward establishing a sustainable international platform for research collaboration, academic exchange, and talent development in the field of mathematics for public health. The establishment of the C2H Network reflects the shared commitment of scholars from China, Canada, and Hungary to advancing interdisciplinary research at the interface of public health, mathematics, complexity science, and artificial intelligence.

The workshop aimed to promote in-depth collaboration on mathematical and AI-driven approaches to public health challenges. Through invited lectures, panel discussions, and academic exchanges, participants discussed how mathematical modelling, complex systems theory, computational science, and artificial intelligence can contribute to the understanding, prediction, prevention, and control of emerging public health risks.

The opening ceremony was chaired by Prof. Wei Lin, Director of the Research Institute of Intelligent Complex Systems at Fudan University. In his opening remarks, Prof. Lin warmly welcomed the participating scholars and emphasized the importance of interdisciplinary collaboration and international academic exchange in addressing complex public health challenges.

During the workshop, leading scholars shared their latest research progress and perspectives. Prof. Yiming Shao from the Chinese Center for Disease Control and Prevention introduced China’s experience and challenges in infectious disease prevention and public health response. Prof. Seyed Moghadas from York University presented recent advances in AI-enabled public health decision-making systems from the Canadian perspective. Prof. Gergely Röst from the University of Szeged, Hungary, discussed mathematical modelling and dynamical systems approaches for understanding infectious disease transmission. Prof. Jianhong Wu from York University shared insights into the role of spatial heterogeneity, population dynamics, and host–vector interactions in disease transmission, highlighting the value of mathematical models in supporting public health risk assessment and intervention design.

The successful convening of this workshop provided an important platform for academic exchange and international collaboration in mathematics and public health. The workshop also laid a solid foundation for continued collaboration within the C2H Network and for future joint research, talent training, and international academic activities. The next workshop is planned to be held in Canada next year, further strengthening the long-term partnership among the participating institutions and scholars.

From May 13 to 17, 2026, the China-Canada-Hungary Joint Workshop on Mathematics of Complexity in Public Health was successfully held at Fudan University, Shanghai. The workshop was jointly organized and supported by the Research Institute of Intelligent Complex Systems, Fudan University; School of Mathematical Sciences, Fudan University; Shanghai Center for Mathematical Sciences; Feishu, China; Fields Institute for Research in Mathematical Sciences, Canada; York University, Canada; Centre of Excellence in Artificial Intelligence for Public Health Advancement (AIPHA), Canada; National Laboratory for Health Security, Hungary; Hungarian National Laboratory; and the Bolyai Institute, University of Szeged, Hungary.

As the first workshop of the Canada-China-Hungary Network of Mathematics for Innovation in Public Health, or the C2H Network, the event marked an important step toward establishing a sustainable international platform for research collaboration, academic exchange, and talent development in the field of mathematics for public health. The establishment of the C2H Network reflects the shared commitment of scholars from China, Canada, and Hungary to advancing interdisciplinary research at the interface of public health, mathematics, complexity science, and artificial intelligence.

The workshop aimed to promote in-depth collaboration on mathematical and AI-driven approaches to public health challenges. Through invited lectures, panel discussions, and academic exchanges, participants discussed how mathematical modelling, complex systems theory, computational science, and artificial intelligence can contribute to the understanding, prediction, prevention, and control of emerging public health risks.

The opening ceremony was chaired by Prof. Wei Lin, Director of the Research Institute of Intelligent Complex Systems at Fudan University. In his opening remarks, Prof. Lin warmly welcomed the participating scholars and emphasized the importance of interdisciplinary collaboration and international academic exchange in addressing complex public health challenges.

During the workshop, leading scholars shared their latest research progress and perspectives. Prof. Yiming Shao from the Chinese Center for Disease Control and Prevention introduced China’s experience and challenges in infectious disease prevention and public health response. Prof. Seyed Moghadas from York University presented recent advances in AI-enabled public health decision-making systems from the Canadian perspective. Prof. Gergely Röst from the University of Szeged, Hungary, discussed mathematical modelling and dynamical systems approaches for understanding infectious disease transmission. Prof. Jianhong Wu from York University shared insights into the role of spatial heterogeneity, population dynamics, and host–vector interactions in disease transmission, highlighting the value of mathematical models in supporting public health risk assessment and intervention design.

The successful convening of this workshop provided an important platform for academic exchange and international collaboration in mathematics and public health. The workshop also laid a solid foundation for continued collaboration within the C2H Network and for future joint research, talent training, and international academic activities. The next workshop is planned to be held in Canada next year, further strengthening the long-term partnership among the participating institutions and scholars.