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Subject offerings of new and developing areas of knowledge in computer science intended to augment the existing curriculum. See Class Schedule or departmental course information for topics and prerequisites. Course Information: May be repeated in the same or separate terms if topics vary.

This graduate topics course aims to take students from the rudiments to some parts of the research frontiers of expansion, coding theory, and optimization from a classical and quantum perspective. Main Topics Expansion: Expander graphs combine two opposing properties of being well-connected yet sparse. This powerful combination leads to various applications in CS (and mathematics), such as error correction, hardness of approximation, fast algorithms, sampling, etc. Recently, several notions of high-dimensional expansion appeared, leading to exciting discoveries. Coding theory: Codes are "robust" collections of strings that not only have implications for protection against errors in communication and storage but also have connections to diverse fields such as complexity theory, expansion, etc. Recently, many breakthrough constructions of codes were discovered, such as explicit binary codes close to the GV bound, good LTCs, and good qLDPC. Optimization: Convex programming, in partic