My work centers on causal inference: I build (mainly computational) tools that predict the results of experiments. This includes computer models in which we simulate systems and manipulate them, and more formal tools like DAGs.
I apply causal inference methods to Immunology, attempting to understand better how the immune system works and how it interacs with pathogens. I find causal inference methods useful because they help to plan and interpret experiments, can integrate experimental data at different scales, and make it possible to at least simulate experiments that we cannot do (yet).
In the past, I also worked in Artificial Immune Systems, where we apply immunological principles and paradigms to problems in computer science and engineering. I still find this interesting and may return to this topic at some point in the future.
PhD in Theoretical Computer Science, 2011
University of Luebeck, Germany