I am a Senior Applied Scientist at Microsoft Office AI, where I focus on advancing intelligent document understanding and generation to enhance workplace productivity. I earned my Ph.D. in Computer Science from Purdue University, advised by Prof. Lin Tan.

My research broadly explores how AI can transform the way software is created, maintained, and used. I develop methods for code generation, automated program repair, and vulnerability detection to accelerate development, reduce errors, and improve software reliability. At Microsoft, I extend these ideas to document intelligence, building systems that help knowledge workers understand, draft, and edit documents more efficiently.

Publications

• [ICSE-2026] Unified Software Engineering agent as AI Software Engineer
  Leonhard Applis, Yuntong Zhang, Shanchao Liang, Nan Jiang, Lin Tan, Abhik Roychoudhury
• [ACL-2025] Can Language Models Replace Programmers? REPOCOD Says 'Not Yet'
  Shanchao Liang, Nan Jiang, Yiran Hu, Lin Tan Data
• [ACL-2025] WAFFLE: Multi-Modal Model for Automated Front-End Development
  Shanchao Liang, Nan Jiang, Shangshu Qian, Lin Tan Model Data
• [ICLR-2025] Nova: Generative Language Models for Assembly Code with Hierarchical Attention and Contrastive Learning
  Nan Jiang, Chengxiao Wang, Kevin Liu, Xiangzhe Xu, Lin Tan, Xiangyu Zhang Model
• [ICRA-2025] SELP: Generating Safe and Efficient Task Plans for Robot Agents with Large Language Models
  Yi Wu, Zikang Xiong, Yiran Hu, Shreyash S. Iyengar, Nan Jiang, Aniket Bera, Lin Tan, Suresh Jagannathan
• [OOPSLA-2025] Show Me Why It's Correct: Saving 1/3 of Debugging Time in Program Repair with Interactive Runtime Comparison
  Ruixin Wang, Zhongkai Zhao, Le Fang, Nan Jiang, Yiling Lou, Lin Tan, Tianyi Zhang
• [AAAI-2025] LATTE: Improving Latex Recognition for Tables and Formulae with Iterative Refinement
  Nan Jiang, Shanchao Liang, Chengxiao Wang, Jiannan Wang, Lin Tan Data Poster
• [NeurIPS-2024] Training LLMs to Better Self-Debug and Explain Code
  Nan Jiang, Xiaopeng Li, Shiqi Wang, Qiang Zhou, Soneya Binta Hossain, Baishakhi Ray, Varun Kumar, Xiaofei Ma, Anoop Deoras Page Poster
• [CCS-2024] ReSym: Harnessing LLMs to Recover Variable and Data Structure Symbols from Stripped Binaries
  🏆 Won ACM SIGSAC Distinguished Paper
  Danning Xie, Zhuo Zhang, Nan Jiang, Xiangzhe Xu, Lin Tan, Xiangyu Zhang Data
• [SANER-2025] How Effective are Large Language Models in Generating Software Specifications?
  Danning Xie, Byungwoo Yoo, Nan Jiang, Mijung Kim, Lin Tan, Xiangyu Zhang, Judy S. Lee Poster
• [NDSS-2025] Unleashing the Power of Generative Model in Recovering Variable Names from Stripped Binary
  Xiangzhe Xu, Zhuo Zhang, Zian Su, Ziyang Huang, Shiwei Feng, Yapeng Ye, Nan Jiang, Danning Xie, Siyuan Cheng, Lin Tan, Xiangyu Zhang
• [FSE-2024] A Deep Dive into Large Language Models for Automated Bug Localization and Repair
  Soneya Binta Hossain, Nan Jiang, Qiang Zhou, Xiaopeng Li, Wen-Hao Chiang, Yingjun Lyu, Hoan Nguyen, Omer Tripp
• [ISSTA-2023] How Effective Are Neural Networks for Fixing Security Vulnerabilities
  Yi Wu, Nan Jiang, Hung Viet Pham, Thibaud Lutellier, Jordan Davis, Lin Tan, Petr Babkin, Sameena Shah Data
• [ICSE-2023] Impact of Code Language Models on Automated Program Repair
  Nan Jiang, Kevin Liu, Thibaud Lutellier, Lin Tan Data
• [ICSE-2023] KNOD: Domain Knowledge Distilled Tree Decoder for Automated Program Repair
  Nan Jiang, Thibaud Lutellier, Yiling Lou, Lin Tan, Dan Goldwasser, Xiangyu Zhang
• [ICSE-2021] CURE: Code-Aware Neural Machine Translation for Automatic Program Repair
  Nan Jiang, Thibaud Lutellier, Lin Tan
• [NMI-2022 (Journal)] Quantifying Spatial Homogeneity of Urban Road Networks via Graph Neural Networks
  Jiawei Xue, Nan Jiang, Senwei Liang, Qiyuan Pang, Takahiro Yabe, Satish V. Ukkusuri, Jianzhu Ma

Preprints

• Collu-Bench: A Benchmark for Predicting Language Model Hallucinations in Code
  Nan Jiang, Qi Li, Lin Tan, Tianyi Zhang Data

Services

• PC Member, AAAI 2026
• PC Member, ASE 2025
• PC Member, CIKM 2025
• PC Member, NeurIPS 2025 Datasets & Benchmark Track
• PC Member, FORGE 2025 Data and Benchmarking Track (Co-located with ICSE 2025)
• PC Member, ICLR 2025
• PC Member, Workshop on Automated Program Repair (Co-located with ICSE 2025)
• PC Member, ASE 2024 Artifact Evaluation Track
• PC Member, SCAM 2024 Research Track
• PC Member, FSE 2023 Artifact Evaluation Track
• Reviewer, TSE 2024 (five times), TSE 2025
• Reviewer, TOSEM 2023, TOSEM 2024 (seven times)
• Reviewer, EISEJ 2024 (twice)
• Reviewer, Open Research Europe 2024

Education

• Ph.D in Computer Science, Purdue University, 2025
• B.S. in Computer Science, Peking University, 2019