About
I am a Ph.D. student in the Augment Research Group at the Department of Computer Science, KU Leuven and imec, supervised by Prof. Katrien Verbert and Dr. Yucheng Jin. I have also been fortunate to collaborate with Dr. Zhen Wang.
My research focuses on how large language models represent and understand individual users, alongside interaction design that supports diverse needs and preferences. More broadly, I aim to make LLMs more personalized, transparent, and controllable for users.
Selected Publications
View All →How Far Do Persona Effects Generalize in Language Models?
Yufan Zhou, Yuxuan Liu, Enze Ma, Lyumanshan Ye, Zhongqi Yue, Robin De Croon, Yucheng Jin, Katrien Verbert, Zhao Wang
arXiv, Sep 2026
Mind2Dialogue: Training Human-Aware Language Models by Simulating User Mental States
Zixuan Wang*, Yufan Zhou*, Jinzhou Tang*, Xinle Yu, Chengjun Wu, Lyumanshan Ye, Zhaoxiang Feng, Letian Peng, Adyasha Patra, Fan Bai, Enze Ma, Zhengding Hu, Jianyang Gu, Zhao Wang, Yufei Ding, Jingbo Shang, Tianmin Shu, Zhiting Hu, Zhen Wang
arXiv, Sep 2026
MemAudit: Auditing Long-Term Agent Memory via Hidden User-State Recovery
Enze Ma*, Yufan Zhou*, Wei-Chieh Huang, Jie Yang, Huanhuan Ma, Zixuan Wang, Chengze Li, Chunyu Miao, Philip S. Yu, Zhen Wang
arXiv, Jun 2026
DeepPersona: A Generative Engine for Scaling Deep Synthetic Personas
Zhen Wang*, Yufan Zhou*, Zhongyan Luo, Lyumanshan Ye, Adam Wood, Man Yao, Saab Mansour, Luoshang Pan
NeurIPS 2025 LAW Workshop (Spotlight), EMNLP 2026 Findings
News
One first-author paper is accepted by UMAP 2026 🎉
Our paper is awarded as a Spotlight at NeurIPS 2025 LAW Workshop 🏅
One co-author paper is accepted by IET Computer Vision 🎉
One co-author paper is accepted by FedCSIS 2024 🎉