Miguel is an ecologist turned network scientist who thinks differently about problem solving. He conducts interdisciplinary research by combining mathematical models, computer simulations, and database analysis, to answer questions that go beyond the traditional boundaries among disciplines, merging ecology with evolution, sociology, genetics, software design, and artificial life.
Currently he is interested in biomedical research, and more specifically, in the idea of controlling evolution to fight disease. That’s why he is trying to develop a general approach to harness the evolution of asexual populations of malignant cells, pathogens, and entire microbial communities by combining mathematical models with digital evolution (i.e., a computational evolutionary framework where self-replicating computer programs—digital organisms—interact, mutate, and evolve within a user-defined computational environment). The ultimate goal of his research is to find general principles that can help researchers working in the lab to fight against human diseases.
Please, feel free to contact Miguel if you are interested in his work.