We study the effects of randomness and uncertainty on complex systems and optimization problems, with techniques at the intersection of applied probability and operations research. Particular attention is given to the area of stochastic processes on interacting networks, queueing theory and the analysis of random walks and higher-dimensional Markov processes. A key goal is to develop analytic, probabilistic, algorithmic and asymptotic methods, with emphasis on asymptotic laws and scaling limits for large-scale critical systems. Typical application areas are computer-communications, energy networks, logistics and service operations, biological systems, particle interactions, and social networks.
Photo by Denys Nevozhai on Unsplash
Photo by Nicholas Cappello on Unsplash
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