I'm a biophysics theorist interested in the development of natural as well as artificial biological systems, and especially in comparing healthy or good development to alternatives.

In early stages of development, cells need to respond to external or internal signals or cues in a reproducible, precise or efficient way. Yet, it is unclear how to evaluate reproducibility, precision and efficiency in complex stochastic systems: for example, different artificial neuronal networks can perform the same task well, or efficiency in response to a signaling molecule can depend on biological constraints that may be invisible to the observer. 

These difficulties in assessing precision and efficiency in development make it difficult to understand what type of architectures or networks different biological systems use to fulfill their task or to develop well. They also pose an impediment to assess artificial or synthetic systems. I'm interested in understanding when biological systems respond precisely or optimally to a given signal, and what tricks they employ. I'm particularly excited by processes on the sub-cellular level, for example on gene regulation and transcription or viral infections, but also by multicellular organisms, such as networks of neurons. 

As a theorist, I like statistical physics, information and probability theory and stochastic calculus. I enjoy exploring simple model systems and find optimal bounds for such systems on the one hand, and predict experimental behaviour on the other. I am happy when I can use experimental data to infer models or classes of models on the other. I collaborate closely with both experimental and theoretical colleagues.