I am a postdoctoral fellow in the RealArt convergence environment where I work at the intersection of machine learning and causal inference applied to biomedical domains. I am also engaged in teaching and master student supervision at the Department.
During my PhD, I worked on machine learning and its application to adaptive immune receptors and repertoires (AIRRs). I developed the immuneML software platform to improve standardization, transparency, and reproducibility of machine learning analysis in the AIRR field. I also look into how the robustness of machine learning approaches in this field can benefit from the causal inference framework.