Research Scientist
Woven by Toyota
I am a Research Scientist at Woven by Toyota, where I work on building intelligent systems that understand and simulate human behavior. My research focuses on developing AI agents that can faithfully reproduce human decision-making patterns, with applications in recommender systems, autonomous systems, and human-AI interaction.
My work bridges the gap between large language models (LLMs) and real-world user behavior. I am particularly interested in how we can train AI agents to internalize world dynamics and align with human preferences through counterfactual reasoning, self-reflection, and intrinsic motivation.
Prior to Woven by Toyota, I worked on reinforcement learning and intrinsic motivation, exploring how agents can learn efficiently through curiosity-driven exploration and hierarchical learning from human feedback.
New paper introducing world-model-driven agents that achieve 52.9% action prediction accuracy (vs. 24.2% prior best) for recommender system evaluation.
Read more →
Our paper on efficient large-scale urban behavior simulation with LLM agents has been accepted to EACL 2026.
Read more →
Our paper on simulating user behavior with large language models for recommender system evaluation has been accepted to ACL 2025.
Read more →
CitySim presents large-scale LLM-driven agent simulation for modeling urban behaviors and city dynamics.
Read more →
arXiv preprint, 2025
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL), 2025
Proceedings of the 2026 Conference of the European Chapter of the Association for Computational Linguistics (EACL), 2026
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2025
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL), 2025
Applied Intelligence, Springer, 2021
Machine Learning, vol. 109, pp. 493-512, Springer, 2020
International Conference on Artificial Neural Networks (ICANN), 2020
ACM Transactions on Intelligent Systems and Technology (TIST), 2024