Spring 2022: Stochastic Processes for the Design and Analysis of Algorithms. Introduction to interplay between stochastic processes and algorithms used in statistics and machine learning. Covers core stochastic processes concepts and use to design and analyze algorithms for sampling and large-scale stochastic optimization. Strong emphasis on practical implications of results.