Research profile

My research focuses on improving the management of prediabetes in clinical practice through the development of new approaches to detection and treatment. The aim is to create an explainable, data-driven algorithm that can identify individuals with prediabetes using easily accessible risk factors without relying on laboratory measurements. This approach has the potential to simplify and make screening and early identification of individuals in need of intervention more cost-effective.

Additionally, I am exploring digital health-based lifestyle interventions as a treatment option for individuals with prediabetes. Digital solutions offer a scalable and more accessible approach to supporting lifestyle changes and reducing the risk of progression to type 2 diabetes.

I strive to develop a comprehensive strategy that improves both the detection and treatment of prediabetes. The goal is to enhance clinical practice with evidence-based solutions that contribute to better prevention and long-term health outcomes.

Teaching profile

I primarily supervise master's students in Clinical Science and Technology as well as medical students working on public health projects using a problem-based learning approach. Additionally, I assist in case-based teaching for medical and MedIS students.