Kangming Li is an Assistant Professor in the Materials Science and Applied Physics department at KAUST. He received his PhD in Physics from Paris-Saclay University and later worked at the University of Toronto as a postdoctoral fellow in Materials Science and Engineering, followed by a role as staff scientist in the Acceleration Consortium. His research focuses on the intersection of artificial intelligence, high-throughput atomistic modeling, and autonomous experimentation. At KAUST, his group develops trustworthy machine-learning methods, AI-driven workflows, and large-scale data approaches to accelerate the design, discovery, and optimization of materials.

Professor Li specializes in integrating artificial intelligence with computationalmodeling to enable and accelerate autonomous research in the physicalsciences. His work emphasizes the creation of robust and efficient machinelearning methodologies for both computational and experimental design.Additionally, he focuses on developing automated workflows and deep learningmodels to accelerate atomistic simulations and enhance materials informatics.His research interests encompass a variety of materials, including structuralmaterials, catalysts, batteries, metal organic frameworks and solar cells.​​