Machine Learning and Statistical Models for Gene-by-Environment Interaction Analysis

My research focuses on developing methods to identify gene-by-environment (GxE) interactions by combining classical statistical approaches with machine learning techniques. While traditional GxE analyses rely on linear mixed models, I work at the intersection of statistical inference and machine learning. This approach aims to improve detection of GxE effects while maintaining clear statistical hypothesis testing.

Tutor in "Introduction to Deep Learning" in winter semester 2024/25.

Tutor in "Advanced Machine Learning Seminar" in summer semester 2025.

Leva, Tobias and Whitmire, Clarissa J and Sauve, Ilaria and Bokiniec, Phillip and Memler, Charlene and Horn, Bibiana M and Vestergaard, Mikkel and Carta, Mario & Poulet, J. F. (2024). The cellular representation of temperature across the somatosensory thalamus. bioRxiv, 2024-02.