J. Ignacio Arroyo; Theoretical and Computational Systems Biology.

 My research is focused on understanding the emergent generic quantitative principles underlying the structure, function, and dynamics of biological systems, from cells to societies and ecosystems. To do so, I use a physical and complex systems perspective together with mathematical and computational modeling. My research has the ultimate goal of making predictions to take informed decisions (e.g., for policy of conservation, restoration, or rural/urban planning), control/regulate, and design biological and social systems. This research agenda often includes searching for statistical patterns and formulating a hypothesis that could explain them. This includes simple patterns that could be described by models such as scaling relationships or power laws. An alternative way is to test existing hypotheses or models. The ultimate goal is to make (deduce) models from fundamental physical principles and derive predictions for the behavior of biological systems, and test them with data. A byproduct of this type of research is the development and integration of databases, making them available to the scientific community, as well as building libraries/packages or apps to analyze the data. For example, currently we are developing a model for the origin of scaling laws in cells, based on fundamental principles of statistical mechanics and optimization. This model can be useful to guide the design of synthetic cells. 

I also have experience in teaching. I have worked as a teaching assistant of the courses "Evolution", "Biostatistics", and "Advanced Biostatistics".The most significant is as a professor of practice of biostatistics, for undergraduate students, a role that I played for 5 years. I have also participated as a mentor for the Santa Fe Institute (SFI) Undergraduate Complexity Research (UCR) program and have offered tutorials in the SFI Complex Systems Summer School.