Explore moment analysis, model reduction techniques, and their application to London's bike-sharing system in this insightful conference talk. Delve into the challenges of reducing complex models across various scientific disciplines to a manageable number of variables for practical computation and accurate prediction. Discover how powerful statistical approaches based on large-scale data analysis are revolutionizing the modeling paradigm. Learn about the emerging combination of statistical inference, high-throughput computation, and physical laws in model development. Examine the mathematical foundations for integrating these methods, with a focus on collective dynamics, molecular modeling, cell biology, and fluid dynamics. Gain valuable insights into bike-sharing systems, user journey planning, Markov queueing models, time-inhomogeneous PCTMCs, moment approximation techniques, and the application of these concepts to London's bike-sharing network. Understand the process of deriving significant station sets, specifying initial states for reduced PCTMCs, and evaluating experimental results. Read more