Yilin Fang
Yilin Fang

About Me

I am Yilin Fang, a first-year Ph.D. student in the Department of Computer Science and Engineering (CSE) at The Ohio State University (OSU), where I am a member of W3CIL Lab under the supervision of Dr. Carter Yagemann. My research focuses on the intersection of computer security and machine learning, particularly in automated vulnerability discovery, analysis and prevention.

Prior to joining OSU, I earned my Master’s degree in Cyberspace Security from the School of Cyber Science and Engineering at Huazhong University of Science and Technology (HUST) in 2023, under the guidance of Dr. Bin Yuan. During my master's program, it was my great fortune to work with Dr. Yueming Wu on source-code-level vulnerability discovery and clone detection. I also completed my Bachelor’s degree in Information Security at HUST in 2020.


  1. Code2Img: Tree-based Image Transformation for Scalable Code Clone Detection
    Yutao Hu, Yilin Fang, Yifan Sun, Yaru Jia, Yueming Wu, Deqing Zou, Hai Jin
    Published in IEEE Transactions on Software Engineering (TSE), vol. 49(9), pp. 4429-4442, 2023
    [DOI] [bibtex] [code]
  2. Fine-grained Code Clone Detection with Block-based Splitting of Abstract Syntax Tree
    Tiancheng Hu*, Zijing Xu*, Yilin Fang, Yueming Wu, Bin Yuan, Deqing Zou, Hai Jin
    (*: under my mentorship)
    Appeared in Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA 2023), Seattle, WA, USA, July 17-21, 2023
    [DOI] [bibtex]
  3. Enhancing Deep Learning-based Vulnerability Detection by Building Behavior Graph Model
    Bin Yuan, Yifan Lu, Yilin Fang, Yueming Wu, Deqing Zou, Zhen Li, Zhi Li, Hai Jin
    Appeared in Proceedings of the 45th IEEE/ACM International Conference on Software Engineering (ICSE 2023), Melbourne, Australia, May 14-20, 2023
    [DOI] [bibtex]


Run the following command in a shell (with Python set up) to get my email address:

$ echo ZmFuZy4xMDA3QG9zdS5lZHU= | python -m base64 -d

Or use the built-in decoder to decode:

Press ENTER key (or click the decode link above) to decode.