Marija Vucelja

Research field: nonequilibrium statistical physics

Lately, Marija has focused on anomalous thermal relaxations of physical systems, systems far from equilibrium, stochastic thermodynamics, phase transitions, and efficient randomized algorithms (such as those utilizing non-reversible Markov Chains) designed for evaluating marginals and inference.

Over the years, Marija studied the mixing and clustering of particles in flows, problems relevant to understanding the formation of rain droplets and planetesimals, clumping of pollutants on water surfaces, and industrial applications. She derived the compressibility of surface flows and described the aggregation-disorder transition of particles in flows. Using “chaotic mixing,” she substantially accelerated specific Monte Carlo algorithms (the main numerical tools for studying complex systems). Next, Marija investigated the emergence of clones in populations. Drawing analogies between glassy systems and population dynamics, she calculated the coalescence rate (the probability of two individuals belonging to the same clone). 

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