- Core requirements: 7 common courses taken by all CMS students (first year)
- Depth requirement: 3 courses in a given area
- Breadth requirement: 3 courses from mathematics, science, engineering, or economics
- Algorithms & complexity: Approximation algorithms, online algorithms, complexity theory, and computability.
- Algorithmic economics: Auctions and mechanism design, algorithmic game theory, and privacy.
- Biological circuits: Organic substrates for computation, including neuronal computing and DNA computing.
- Feedback & control: Robust control, feedback, dynamical systems theory.
- Inference & statistics: Statistical decision theory, information theory, and adaptive signal processing.
- Information systems: Information theory, coding theory, communication, and signal processing.
- Machine learning & vision: Algorithmic, mathematical, and biological perspectives on computational models for learning and vision.
- Networked systems: The study of complex networks, in fields ranging from biology, social science, communications, and power.
- Optimization: Convex optimization, conic and discrete optimization, and numerical methods for largescale optimization.
- Quantum information theory: Quantum algorithms and complexity, convex optimization, and operator theory.
- Scientific computing: Computational methods for problems arising in the physical sciences, partial differential equations.
- Uncertainty quantification: Markov chains and martingales, stochastic system analysis, and convex optimization.