Research Interests
Developing novel next-generation of BPA-free dental restorative materials, including dental adhesives, composites and calcium-silicate materials. Systematically evaluating the physico-chemical properties, biocompatibility, and bioactivity of commerical restorative materials.
Deciphering neuroimmune crosstalk in pulpitis and translate these insights into mechanism-informed strategy for vital pulp therapy. We are also developing a point-of-care biosensing platform to diagnose pulpal inflammation, which will help clinicians identify appropriate cases for vital pulp therapy.
Applying machine learning and radiomics to build the first interpretable AI-assisted model for predicting the 12-month outcome of root canal retreatment. Validating with multi-centre datasets to evaluate the generalizability of the model, with the ultimate goal to assist clinical decision making.
Implementing agumented reality, static guides, dynamic navigation and robotics in endodontic treatment and education. By integrating these advanced technologies with clinical expertise, we aim to enhance accuracy, predictability, and minimally invasive dental care.