Kevin(Jian) Lu

Master's Student · Duke University

I am a Master's student in Computer Science at Duke University, where I am fortunate to be advised by Professor Anru Zhang. My research interests span three directions:

  • AI for Health — electronic health record (EHR) data quality, where I formulate and build automated methods to detect documentation inconsistencies in clinical records.
  • Efficient LLM Inference and Explainability — I investigate where and how information is encoded inside large language models, using these insights to improve both interpretability and inference efficiency.
  • LLM Agents — text-to-SQL generation, formulated as an LLM-agent workflow that reasons over databases to translate natural-language questions into SQL.

My long-term goal is to build more efficient and principled AI systems through the theoretical study of models such as large language models, ultimately better supporting real-world applications such as biomedical informatics and healthcare.

Previously, I obtained my B.S. in Computer Science from the University of Rochester, where I worked with Professor Jiebo Luo on computer vision methods for biomedical image analysis.

Selected Publications

Preprint · Under Review Submitted to JAMIA
Toward Automated Detection of Documentation Inconsistencies in Electronic Health Records
Jian Lu, Panyu Chen, Miriam Treggiari, Robert Blessing, Danyang Zhuo, Chunhua Weng, William W. Stead, Anru R. Zhang
2026 IEEE International Conference on Healthcare Informatics (ICHI)
Reliable Curation of EHR Dataset via Large Language Models under Environmental Constraints
Raymond M. Xiong, Panyu Chen, Tianze Dong, Jian Lu, Louis Hu, Nathan Yu, Benjamin Goldstein, Danyang Zhuo, Anru R. Zhang
2025 ICLR 2025 Workshop on Data Problems
Revisiting Multi-Modal LLM Evaluation
Jian Lu, Shikhar Srivastava, Junyu Chen, Robik Shrestha, Manoj Acharya, Kushal Kafle, Christopher Kanan

Education

2025 — Present
M.S. in Computer Science
Duke University, Durham, NC
Advisor: Prof. Anru Zhang. Research focus on AI for Health, efficient AI agent workflows, and scalable reasoning in large language models.
2021 — 2025
B.S. in Computer Science
University of Rochester, Rochester, NY
Worked with Prof. Jiebo Luo on computer vision methods for biomedical image analysis.

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