Grant Schoenebeck

Associate Professor, School of Information

Information Mechanism Design and Machine Learning

My current research combines machine learning tools and economic approaches (e.g game theory, mechanism design, and information design) to develop and analyze systems for eliciting and aggregating information from of diverse group of agents with varying information, interests, and abilities.
This work applies to scenarios where a collective decision-making process is required, such as peer grading, peer review, crowd-sourcing, content moderation, misinformation detection, surveys, and employment hiring/evaluation.
More broadly, I am interested in multi-agent systems, a subfield of AI; data economics; and algorithmic game theory.