EE-619: Advanced topics in network neuroscienceThe main goal of this course is to give the student a solid introduction into approaches, methods, and tools for brain network analysis. The student will learn about principles of network science and
MATH-360: Graph theoryThe course aims to introduce the basic concepts and results of modern Graph Theory with special emphasis on those topics and techniques that have proved to be applicable in theoretical computer scienc
MATH-410: Riemann surfacesThis course is an introduction to the theory of Riemann surfaces. Riemann surfaces naturally appear is mathematics in many different ways: as a result of analytic continuation, as quotients of complex
CS-455: Topics in theoretical computer scienceThe students gain an in-depth knowledge of several current and emerging areas of theoretical computer science. The course familiarizes them with advanced techniques, and develops an understanding of f
COM-405: Mobile networksThis course provides a detailed description of the organization and operating principles of mobile and wireless communication networks, as well as the use of wireless signals for sensing and imaging.
MATH-467: Probabilistic methods in combinatoricsThe 'probabilistic method' is a fundamental tool in combinatorics. The basic idea is as follows: to prove that an object (for example, graph) with certain properties exists, it suffices to prove that
MATH-260(b): Discrete mathematicsStudy of structures and concepts that do not require the notion of continuity. Graph theory, or study of general countable sets are some of the areas that are covered by discrete mathematics. Emphasis
