Pennsylvania State University

The Foundations of Artificial Intelligence Research Lab (FAIR) @ Penn State conducts foundational research at the intersection of artificial intelligence, economics, and computation. Our goal is to design novel principled solutions for robust and fair decision-making in the presence of multiple intelligent entities (e.g., humans, robots, or autonomous agents). These AI solutions have profound impact on several real-world applications ranging from healthcare resource allocation and refugee placement to recommendation systems and gig economies.

Public Platforms

MatchXplain

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MatchU.ai

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Projects

Algorithmic Fairness: Theoretical Foundations

Class Fairness in Online Matching, AIJ 2024 [paper]
Ordinal Maximin Share Approximation for Goods, JAIR 2022 [paper]
Non-Monotonicity in Fair Division of Graphs, AAAI 2026 [paper]
Fairly Allocating Goods and (Terrible) Chores, IJCAI 2023 [paper]

Reasoning and Preferences in Generative AI

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Distributive Fairness in Large Language Models: Evaluating Alignment with Human Values, NeurIPS 2025 [paper]
Matching Markets Meet LLMs: Algorithmic Reasoning with Ranked Preferences, NeurIPS 2025 [paper]

Human-Centered Fairness in Multiagent Systems

Bridging Theory and Perception in Fair Division: A Study on Comparative and Fair Share Notions, arXiv [paper]
Epistemic vs. Counterfactual Fairness in Allocation of Resources, ACM EAAMO 2025 [paper]

Strategic Reasoning in Matching Markets

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Accomplice Manipulation of the Deferred Acceptance Algorithm, IJCAI 2021
[paper]
Two for One & One for All: Two-Sided Manipulation in Matching Markets, IJCAI 2022
[paper]

Learning Agent Preferences in Competing Markets

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Putting Gale & Shapley to Work: Guaranteeing Stability Through Learning, NeurIPS 2024 [paper]
Bandit Learning in Matching Markets: Utilitarian and Rawlsian Perspectives, arXiv 2025 [arXiv]

Second-Order Information in AI

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The Surprising Effectiveness of SP Voting with Partial Preferences, NeurIPS 2024 [paper]
Surprisingly Popular Voting Recovers Rankings, Surprisingly!, IJCAI 2021 [paper]

Gig Economy: Fair Distribution of Tasks on Graphs

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Fair distribution of delivery orders, AIJ 2025 [paper]

AI/CS Education and Pedagogy

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Mind the Gap: the Illusion of Skill Acquisition in Computational Thinking, SIGCSE 2023 [paper]
Are You Game? Assessing Students’ Perception of Learning, Instructors’ Perspective, and Learning Attitude, SIGCSE 2019 [paper]
Learning IS child's play: Game-based Learning in Computer Science Education, ACM TOCE [paper]

Click for a complete list of publications:

Publications

Members

Past summer Interns/REU Students

Alexander Adams, CMU: Summer 2022
Spencer Renenger, Cornell University: Summer 2022
Ronak Singh, Penn State: Summer 2022
Austin Hayes, University of Maryland, College Park: Summer 2021
Fatima Umar, Rochester Institute of Technology: Summer 2021
Nathan Ganger, University of Mount Union: Summer 2021
Sunand Raghupathi, Columbia University: Summer 2019
Gabriella Alexis, Hunter College: Summer 2019

Interested in joining our group:

Join FAIR Lab

Sponsors:

National Science Foundation

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