Li Zhou has a Bachelor's degree from Sichuan University and a Doctorate from Zhejiang University and is a postdoctoral fellow of Cambridge University Singapore Smart Carbon Reduction Center. She has long been engaged in the construction of multi-scale (including molecular scale, unit scale, process scale, and factory scale) high-fidelity mathematical models of chemical process systems that integrate process mechanisms and data, as well as the theoretical research and application technology development of system coupling integration design and optimization based on multi-scale digital models. She has published more than 30 SCI papers in high-level academic journals at home and abroad in the field, presided over one National Youth Fund, one national key research and development plan sub-project, and nineteen enterprise technology development and transformation projects.
Her main research direction includes AI for the engineering of process systems. Aiming at the problem that the integration of chemical energy and mass transfer process is interfered with by process uncertainty, and the model size and computational complexity are restricted, research on intelligent modeling integrating process mechanisms and data is carried out, and the high-fidelity agent model is built at multiple scales, such as unit, device, and process, to help realize the digitalization of chemical process systems that are intelligent, flexible and low-carbon.
Li Zhou has a Bachelor's degree from Sichuan University and a Doctorate from Zhejiang University and is a postdoctoral fellow of Cambridge University Singapore Smart Carbon Reduction Center. She has long been engaged in the construction of multi-scale (including molecular scale, unit scale, process scale, and factory scale) high-fidelity mathematical models of chemical process systems that integrate process mechanisms and data, as well as the theoretical research and application technology development of system coupling integration design and optimization based on multi-scale digital models. She has published more than 30 SCI papers in high-level academic journals at home and abroad in the field, presided over one National Youth Fund, one national key research and development plan sub-project, and nineteen enterprise technology development and transformation projects.
Her main research direction includes AI for the engineering of process systems. Aiming at the problem that the integration of chemical energy and mass transfer process is interfered with by process uncertainty, and the model size and computational complexity are restricted, research on intelligent modeling integrating process mechanisms and data is carried out, and the high-fidelity agent model is built at multiple scales, such as unit, device, and process, to help realize the digitalization of chemical process systems that are intelligent, flexible and low-carbon.