In recent years, complex networks theory has moved from being a theoretical field of research to an applied one. This new relationship is beneficial in a bidirectional way: not only networks yield strategies to make real systems more efficient and robust; real systems also return back new problems that force researchers to develop novel theoretical approaches. In this talk I will review how this process has shaped my recent research activities. I will start by reviewing some major results in neuroscience, and how idiosyncrasies of the human brain have compelled me to merge complex networks theory and data mining to improve functional representations of information processing. I will then move to air transport, and discuss how those concepts can be used to model delay propagation as an information processing problem. I will finally lay out my research plan for the next five years, highlighting the interactions with fields like non-linear time series analysis, information theory and computer science.
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