Machine-Learning-Aided Concrete Mixture Optimization

Junfei Zhang is Professor and PhD supervisor at Guangzhou University/Hebei University of Technology, China. He holds a Bachelor’s and Master’s degree from the University of Science and Technology Beijing, China and a PhD from the University of Western Australia. His primary research focuses on intelligent construction and the utilization of solid waste resources.
He has always studied machine learning-aided concrete mixture optimization. He has been recognized as Stanford’s top 2% most highly cited scientist and has led one National Natural Science Foundation project, four provincial and ministerial projects, and two provincial education reform projects. Prof Zhang serves as editorial board member for several Science Citation Index (SCI) journals, and has published over 100 high-level SCI papers, including 10 highly cited papers with H-index over 40.

Yongshun Zhang is a postgraduate student at Hebei University of Technology, China. He holds a Bachelor’s degree in Civil Engineeringfrom Tianjin Chengjian University, China, and is currently advancing his expertise in sustainable construction materials. His research focuses on machine learning-driven optimization of fly ash-based geopolymer concrete.
He actively contributes to key research projects investigating high-performance, low-carbon alternatives to traditional concrete. Yongshun has co-authored 10 publications in SCI papers and international conference proceedings.