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I am an Assistant Professor in the School of Computer Science at Peking University, where I lead the PKU Interpretable Large Language model And Reasoning (PILLAR) Group in the Institute of Computational Linguistics (ICL).

My current research focuses on natural language processing, machine learning, large language model, and explainable AI. Our goal is to uncover the mechanisms behind large language model and use that understanding to build trustworthy models that are reliable, truthful, and safe. Specifically, we are interested in the following research topics:

• Mechanistic Study of LLMs: How can we open the black box of LLMs to uncover their internal mechanisms, especially those enabling complex reasoning?
• Trustworthy LLMs Guided by Mechanism: How can insights from mechanistic understanding be translated into practice for building LLMs that are reliable, truthful, and safe in real-world applications?

Before joining PKU, I was an Assistant Professor at the College of Information Science, University of Arizona and a postdoctoral scholar in the NLP Group at the University of California, Santa Barbara (UCSB), advised by William Yang Wang. I received my Ph.D. from the National University of Singapore under the supervision of Min-Yen Kan and Tat-Seng Chua. Earlier, I earned an MEng degree from Tsinghua University (advised by Juanzi Li and Jie Tang) and a BEng degree from Beihang University.

潘亮铭博士，北京大学计算机学院助理教授、研究员、博士生导师，国家级青年人才项目（海外）获得者，北京大学博雅青年学者。主要研究方向包括自然语言处理、机器学习、大语言模型与可解释人工智能等，在国际顶级会议期刊发表论文50余篇，Google Scholar总引用量超过4000次。常年担任NeurIPS、ACL、EMNLP、NAACL等顶级学术会议的领域主席。论文曾获ACL 2025 SAC Highlights Award、NeurIPS 2024 Workshop最佳论文奖、IJCNLP-AACL 2023 Area Chair Award。潘亮铭博士本科毕业于北京航空航天大学软件学院，硕士毕业于清华大学计算机系，2022年获得新加坡国立大学计算机科学博士学位，曾于2022年至2025年先后担任美国加州大学圣塔芭芭拉分校博士后研究员、美国亚利桑那大学信息科学学院助理教授。