Teaching

My teaching experience combines formal practical instruction, open educational infrastructure, and research-oriented mentorship. I am especially interested in computational teaching formats where conceptual understanding is reinforced through executable examples, reproducible code, and project-based learning.

Teaching contributions

• practical instruction in Graph Theory

• practical instruction in Advanced Methods in Bioinformatics

• mentoring in cheminformatics, machine learning, molecular docking, graph representations, and molecular modeling

• support for project design, workflow development, interpretation, and scientific writing

Educational resources

SynEdu is being developed as a research-oriented educational platform for executable talktorials in graph-theoretical reaction modeling and computational molecular science. It reflects my view that educational resources can also serve as reusable research infrastructure.

Teaching perspective

I aim for teaching that is rigorous, computationally hands-on, and well integrated with active research practice. In interdisciplinary areas, students benefit from seeing not only the theory but also the workflow logic, the data assumptions, and the limits of the methods being used.