Algorithmic Economics

Market design, the engineering arm of economics, benefits from an understanding of computation: complexity, algorithms, engineering practice, and data. Conversely, computer science in a networked world benefits from a solid foundation in economics: incentives and game theory.

Increasingly, online service design teams require dual expertise in social science and computer science, adding competence in economics, sociology, and psychology to more traditionally recognized requirements like algorithms, interfaces, systems, machine learning, and optimization. Our researchers combine expertise in computer science and economics to bridge the gap between modeling human behavior and engineering web-scale systems.

Scientists with hybrid expertise are crucial as social systems of all types move to electronic platforms, as people increasingly rely on programmatic trading aids, as market designers rely more on equilibrium simulations, and as optimization and machine learning algorithms become part of the inner loop of social and economic mechanisms.

Application areas include auctions, crowdsourcing, gaming, information aggregation, machine learning in markets, market interfaces, market makers, monetization, online advertising, optimization, polling, prediction engines, preference elicitation, scoring rules, and social media.

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People
Sébastien Lahaie
Sébastien Lahaie

David Pennock
David Pennock

Justin Rao
Justin Rao

David Rothschild
David Rothschild

Alex Slivkins
Alex Slivkins

Vasilis Syrgkanis
Vasilis Syrgkanis