Revision in progress...tl;dr - I work in the broad field of complex dynamical systems. So far, I've worked on a cellular automata model of excitable media, and a networked system of chaotic maps. I've some experience with evolutionary algorithms (python-DEAP) as well. I am interested to work on biological or socioeconomic models to understand emergent dynamics.Details:I am studying the emergence of self sustained persistent oscillations in the Greenberg-Hastings cellular automata, which is a spatially extended model of coupled, discrete excitation-relaxation oscillators. Such discrete dynamics qualitatively emulate the behaviour of many systems observed in the real world, such as neurons and cardiac cells.I have found such models offer insights into the role of individual dynamics on emergent phenomena, such as the system’s spatio-temporal “memory” of the patterns of oscillation. I am curious about which individual dynamical features lead to specific kinds of complex behaviour. My current effort is to understand the dependence of probability of persistent oscillations (which is a global, asymptotic phenomena), on the parameters of the simple dynamics at the level of individual cells.I am also working with networks of iterated maps, and I find the role of various coupling schemes, and the system’s collective response to it, to be of particular interest. I have studied a coupling form to generate large fluctuations in networked systems of chaotic logistic maps, and would like to further probe the effect of such coupling forms on the emergent dynamics. In my recent studies, I have been studying the effect of modulation of the coupling between logistic maps, on the emergent dynamics of the network.