Teaching
Graduate teaching and educational resources.
My teaching focuses on causal inference, regression methods, and spatial epidemiology, with an emphasis on conceptual understanding, reproducible data analysis in R, and applying modern statistical methods to real-world public health problems. I teach graduate- and doctoral-level courses in biostatistics at the University of Gothenburg.
Areas of Teaching
🧠 Causal Inference
Counterfactual reasoning, mediation, modern causal inference methods, and sensitivity analysis.
📈 Regression & Survival Analysis
Regression modeling, generalized linear models, survival analysis, model diagnostics, and interpretation.
🗺 Spatial Epidemiology
Disease mapping, Bayesian spatial models, GIS, spatial statistics, and applications in population health.
Current Teaching
| Semester | Course | Role |
|---|---|---|
| Spring 2026 | STA210 – Causal Inference | Course Leader |
| Spring 2026 | SM00133 – Regression Methods II: Logistic and Cox Regression | Course Leader |
| Autumn 2026 | MGH311 – Applied Epidemiology and Biostatistics | Spatial Epidemiology module |
| Autumn 2026 | STA530 – Spatial Epidemiology | Course Leader |
| Autumn 2026 | MGH102 – Quantitative and Qualitative Methods; MPH221 – Epidemiology and Biostatistics | Biostatistics part |
| Autumn 2026 | SFUOBL4 – Introduction to Research Theory and Quantitative and Qualitative Design | Seminar instructor |
Recommended Reading
A comprehensive open-access textbook for learning spatial data analysis in R.
Kolak, M., Menghaney, M., Li, A., & Lin, Q. (2020).
Additional lecture materials and tutorials will be added over time.