Khalid Ferji is an Associate Professor (HDR) in polymer chemistry at Université de Lorraine (ENSIC, LCPM). His research focuses on the design and self-assembly of functional polymers, with expertise spanning controlled radical polymerization, polysaccharide-based nanomaterials, and photo-RAFT PISA. He obtained his PhD in 2013 and his Habilitation (HDR) in 2022.
Over the past decade, he has contributed to the development of polysaccharide-based nanocarriers, light-driven polymerizations, and polymer self-assembly, and more recently has pioneered the integration of artificial intelligence and machine learning into polymer chemistry. His group develops workflows for AI-assisted polymer synthesis, automated characterization, and open-source platforms such as DetectNano.
Khalid has published over 40 research articles in international journals, and is the pedagogical coordinator of the Master’s program CHIPS at Université de Lorraine, where he initiated the AIPOly track at the interface of polymers and AI. Beyond research and teaching, he currently serves as President of the Eastern Section of the French Polymer Group (GFP), contributing to the structuring and visibility of the French polymer community.
His work aims to establish new sustainable and digital approaches for polymer discovery, while fostering stronger links between chemistry, data science, and the broader materials science community.
Research Themes
- Polymer synthesis and self-assembly – Design of functional polymers via controlled radical polymerization, photo-RAFT, and polymerization-induced self-assembly (PISA).
- Physico-chemistry of polymers – Understanding polymer morphology, colloid science, and advanced characterization methods.
- AI-driven polymer informatics – Machine learning for predicting polymerization outcomes, morphologies, and guiding experimental design.
- Continuous-flow polymerization and automation – Coupling flow chemistry with AI and automated characterization for reproducibility and sustainability.