Professional narrative
I use models to make assumptions discussable: how people move through infrastructure, how uncertainty changes a decision, how spatial processes generate patterns, and how students learn to move from an open question to a reproducible argument.
The public website curates manually reviewed explanations and approved figures. Code, notebooks, calculations, and reproduction notes remain in a private technical workspace so the publishing layer does not expose unfinished research material.
Teaching and mentoring
My teaching emphasizes problem formulation, baseline models, units, computational checks, sensitivity analysis, and honest limitations. Competition cases can be valuable, but they are treated as practice in reasoning rather than automatic evidence of publication or deployment.
A recent mentoring outcome is a student-team paper listed as Paper ID 7 in the AI4Nature@AVSS 2026 oral programme, where I am also listed as a co-author.
CV summary
Current focus: secondary mathematics education; mathematical modeling; computational experiments; teaching resources; student research mentoring.
Methods used across the repositories: differential equations, numerical analysis, network models, optimization, stochastic simulation, sensitivity analysis, Python, C++, and notebooks.
This web summary intentionally omits affiliations, awards, publications, and credentials that are not confirmed by the research record. For a current formal CV, please request it by email.