My research concerns the evolution of information. I spend a lot of time thinking of how information is organised, used, and misused.
To be more specific: I develop new computational tools to study the media we produce and consume, the beliefs we hold, the stories we tell, the language we use, as well as the opinions, ideas, and narratives we propagate – how they develop, and how they evolve.
In doing so, I combine tools and approaches from data science, mathematical modelling, complex systems, algorithmic information theory, evolutionary biology, cultural evolution, cultural sociology, political communication, social psychology, cognitive psychology, and broadly speaking, computational social science.
At a more fundamental level, I am also interested in the limitations of theoretical models, and have conducted research on the biases of mathematical models, deep neural networks, and other input-output (e.g. parameter-behaviour) maps.
Prior to that, my work has ranged from high-performance computing in systems biology, to urban mobility and data science, to quantifying political volatility using natural language processing, to investigating how evolutionary search is so efficient (or why evolution works at all).
For more detail and ongoing projects, see the CC Lab website.