About

I have always been drawn to statistical modelling as a way of detecting patterns and associations between variables that clinical judgement alone can miss. When I began my PhD in 2013, I chose to use artificial intelligence to improve diagnostic methods, at a time when it was rarely applied in dental research. I have kept to that direction since, treating machine learning as an adjunct to clinical diagnosis and treatment planning rather than as an end in itself. What matters to me is whether a model holds up against clinical reality, and whether it improves the quality of care a patient receives.

My current work follows three related threads. The first is predictive modelling and neural network applications in orthodontics, the second is growth modification and interceptive orthodontics, where early intervention can greatly change what treatment is later required, and the third is dental education itself: how clinical training is delivered, what students make of it, and what the clinical teacher actually contributes to a student's development.

Earlier projects took me through three-dimensional mapping of the dental arches and palate, occlusal developmental anomalies, geometric morphometric analysis of facial hard and soft tissues, and the orthodontic miniscrew cover, which I carried from bench testing through to a randomised controlled trial and a patent.

Since the beginning of my role as an academician, I have believed that the relationship between lecturer and student should be cordial and grounded in mutual respect rather than authority, and that the lecturer's role goes beyond delivering knowledge to being a mentor. Students should feel free to ask questions and to discuss what they are learning. An environment of intimidation diminishes a student's enthusiasm, sometimes to the point where they avoid asking for guidance at all, and that carries real consequences for their proficiency and for the quality of treatment they provide in clinical training.

I want students to think critically, analytically, and independently. A student who is invited to question current practice learns to examine it rather than simply absorb it, and it is from that habit that leaders in the profession emerge. I also believe students should see that the same clinical situation can be approached in more than one sound way, provided each approach adheres to the guidelines of best clinical practice. That understanding prepares them to analyse what they are taught and to adopt advances as they come.

I value creative thinking almost as highly as content mastery, and encourage students to find novel ways of demonstrating what they know. Breaking down the barriers between individual topics, so that knowledge carries across them, is essential to that.

My goal is to prepare students for clinical practice in a learning environment that is interactive and engaging, with an emphasis on problem solving and critical thinking. I work to create that environment in every course I teach, drawing on a variety of methods to reach different learners, and I give students as much exposure as I can to real clinical reasoning through case-based evaluations and case-based quizzes.

Beyond any single course, I hope students leave with a desire for lifelong learning, not only to keep pace with the latest in the dental field, but to be among those who advance the profession. The same conviction shapes the rest of my academic work: the postgraduate orthodontics curriculum I helped design, the online courses I have built, and the postgraduate and undergraduate researchers I supervise.