Andrew Perrault
Computer Science · The Ohio State University
Publications
94
Citations
388
Est. group size
~2
Recurring co-author estimate
Active years
15
Publishing since 2012
Andrew Perrault works on artificial intelligence methods for decision-making under uncertainty, including reinforcement learning, multi-armed bandits (algorithms that balance exploring options versus exploiting known good ones), and robust optimization for real-world resource allocation problems like city services and conservation. Recent work also touches on language model personalization and verifying distributed computing protocols. Much of the research aims to apply AI techniques to social-impact problems such as public service scheduling and conservation decision-making.
Publication output has fluctuated over the past decade with a notable spike in 2020 and again in 2024-2026, suggesting an active and currently growing publication pace rather than a steady or slowing one.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Learning Provably Correct Distributed Protocols Without Human Knowledge
Open MIND · 2026
- Learning Provably Correct Distributed Protocols Without Human Knowledge
arXiv (Cornell University) · 2026
- Optimizing Urban Service Allocation with Time-Constrained Restless Bandits
Proceedings of the AAAI Conference on Artificial Intelligence · 2026
- Many Preferences, Few Policies: Towards Scalable Language Model Personalization
arXiv (Cornell University) · 2026
- Many Preferences, Few Policies: Towards Scalable Language Model Personalization
arXiv (Cornell University) · 2026
- Recovering Physical Dynamics from Discrete Observations via Intrinsic Differential Consistency
arXiv (Cornell University) · 2026
- Recovering Physical Dynamics from Discrete Observations via Intrinsic Differential Consistency
arXiv (Cornell University) · 2026
- VISTA: Verification In Sequential Turn-based Assessment
Underline Science Inc. · 2026
- The Next Wave of AI for Social Impact: Challenges and Opportunities
IEEE Intelligent Systems · 2025
- Optimizing Urban Service Allocation with Time-Constrained Restless Bandits
arXiv (Cornell University) · 2025
- Cultivating Archipelago of Forests: Evolving Robust Decision Trees Through Island Coevolution
Proceedings of the AAAI Conference on Artificial Intelligence · 2025
- Leaving the Nest: Going beyond Local Loss Functions for Predict-Then-Optimize
Proceedings of the AAAI Conference on Artificial Intelligence · 2024
- Coevolutionary Algorithm for Building Robust Decision Trees under Minimax Regret
Proceedings of the AAAI Conference on Artificial Intelligence · 2024
- Symmetric Reinforcement Learning Loss for Robust Learning on Diverse Tasks and Model Scales
arXiv (Cornell University) · 2024
- Cultivating Archipelago of Forests: Evolving Robust Decision Trees through Island Coevolution
arXiv (Cornell University) · 2024
- arXiv (Cornell University)×39
- Proceedings of the AAAI Conference on Artificial Intelligence×9
- Underline Science Inc.×3
- SSRN Electronic Journal×2
- medRxiv×2
- Jiayu Chen
Computer Science · Purdue University West Lafayette
- Joe Eappen
Computer Science · Purdue University West Lafayette
- Zikang Xiong
Computer Science · Purdue University West Lafayette
- Qinbo Bai
Computer Science · Purdue University West Lafayette
- Tengyu Xu
Computer Science · The Ohio State University
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 19, 2026.
Claim or correct this profile