Haolin Liu
Scholar

Haolin Liu

Google Scholar ID: DgvwKhgAAAAJ
University of Virginia
Reinforcement LearningMachine LearningMechanism Design
Citations & Impact
All-time
Citations
65
 
H-index
4
 
i10-index
4
 
Publications
13
 
Co-authors
11
list available
Resume (English only)
Academic Achievements
  • An Improved Model-Free Decision-Estimation Coefficient with Applications in Adversarial MDPs (2025, Preprint)
  • One Token to Fool LLM-as-a-Judge (NeurIPS 2025 MATH-AI Workshop)
  • Decision Making in Hybrid Environments: A Model Aggregation Approach (COLT 2025)
  • Beating Adversarial Low-Rank MDPs with Unknown Transition and Bandit Feedback (NeurIPS 2024)
  • Corruption-Robust Linear Bandits: Minimax Optimality and Gap-Dependent Misspecification (NeurIPS 2024)
  • Towards Optimal Regret in Adversarial Linear MDPs with Bandit Feedback (ICLR 2024, Spotlight)
  • Bypassing the simulator: Near-optimal adversarial linear contextual bandits (NeurIPS 2023)
Background
  • Third-year PhD student in the Department of Computer Science at the University of Virginia
  • Research centered on Reinforcement Learning (RL), spanning both theoretical and practical domains
  • Theoretical focus: advancing understanding of how RL algorithms learn and adapt in dynamic environments
  • Practical focus: applying RL to post-training of large language models (LLMs), with emphasis on alignment and reasoning
  • Also has experience in game theory and mechanism design