Ariel Procaccia

Ariel Procaccia

Associate Professor

Office: 7713 Gates & Hillman Centers


Phone: (412) 268-5636

I am interested in the mathematical foundations of artificial intelligence, and mainly think about questions at the (pairwise) intersections of AI, social choice, and game theory. Specifically, my research interests include, but are certainly not limited to: multiagent systems, computational social choice and preference handling, computational mechanism design and fair division, machine learning, social networks and reputation systems, decision making under uncertainty, and human computation.
Some examples of projects I am currently working on:

Dynamic social choice: I am augmenting social choice theory using models and techniques from the AI research on decision making under uncertainty to create and analyze new social choice models where preferences can change dynamically.

Incentives in machine learning: I am studying the role of incentives play in machine learning, and designing machine learning algorithms that are immune to manipulation by strategic agents.

Voting and human computation: I wish to design optimal voting rules for use in online labor markets such as Amazon Mechanical Turk.

Fair division of resources: How does one cut a cake fairly? This is a long-standing question that is algorithmic in nature but has received little attention from computer scientists. Related issues include allocation of shared resources in cloud computing environments.