My teaching experience spans core medical education, computational science, and translational biomedical research. I have contributed to teaching in core medicine to medical students, with a focus on building strong clinical reasoning, a clear understanding of pathophysiology, and the ability to apply foundational knowledge to real patient care scenarios.

In parallel, I have contributed to teaching in artificial intelligence, machine learning, computational biology, and mathematical modelling in a biomedical context, helping students and junior researchers understand how quantitative and computational methods can be used to investigate complex disease processes. I am particularly interested in teaching how data-driven approaches can support research in oncology, hepatology, and precision medicine.

I also enjoy teaching related areas such as research methodology, biostatistics, scientific writing, critical appraisal of the literature, translational medicine, and biomarker-focused research design. My teaching approach is interdisciplinary and application-focused, aiming to connect medicine, mathematics, and computation in a way that is rigorous, practical, and clinically meaningful.