Jan Humplík

The traditional paradigm in physics is to build a mathematical model of a given system and then experimentally test the model predictions. Thanks to its success in physics, there was a hope that the same model building approach could be applied in the study of biological systems. Unfortunately, such attempts have been far less glorious, demonstrating the need for new quantitative methods of analyzing biological systems. One possible technique is to focus only on quantities such as entropy that can be inferred directly from data without many assumptions about the underlying system. In particular, these methods are powerful in the study of information processing in biological systems, which is one of the questions I am interested in as a graduate student in the group of Gasper Tkacik at IST Austria. Before I joined IST Austria, I studied theoretical physics at the Faculty of Mathematics and Physics in Prague. Thanks to Bakala Foundation's Scholarship I was able to spend a semester studying at Harvard University and consequently also to return to Harvard and conduct research in the group of Martin Nowak with whom I collaborate to this date.