Networks and Markets / Spring 2026
Course Description
This course considers computing challenges related to incentives, networks, crowds, and markets, with a focus on how these questions interact with algorithms and data-driven methods in applications such as online markets, social media, and civic systems. The course will cover the foundations of game theory and network theory, and then applications in matching markets, online platforms, recommendation systems, and democratic systems. The course will be a combination of applied mathematical modeling of such systems and reading research papers related to these topics in practice.
Important links
- Course website
- Canvas
- Ed Discussion – Primary communication tool
- Gradescope – Place to turn in assignments
Course topics
- Game Theory (~3 weeks)
- Networks (~3 weeks)
- Matching Markets and Online Platforms (~3 weeks)
- Recommendation Systems (~3 weeks)
- Social Choice, Democracy, and Crowdsourcing (~3 weeks)
Previous Offerings
Instructor
Teaching Assistants
Mikhail Fadin
Ulysse Hennebelle