About me
Hi there👋 I am Zihan Fang (房梓晗). I am a Ph.D. candidate in Computer Science at Vanderbilt University, guided by Dr. Yu Huang. I earned my Bachelor's degree in Information Management from Soochow University, and my Master's degree in Data Science from Vanderbilt University. My research develops human-centered AI that lowers barriers to expertise and participation in software engineering. I combine large-scale repository mining, cognitive and behavioral modeling, and reinforcement learning to understand how people develop expertise and translate these insights into AI-supported programming systems and immersive learning environments, with particular attention to novices. Feel free to contact me if you are interested in my work!
Publications
Toward Inclusive Programming Support for Novice Programmers with Dyslexia: Insights from a Comparative Study. ASE 2026
Zihan Fang, Janice Chung, Ruijia Chen, Marcia Barnes, Yuhang Zhao, Yu Huang
[PDF]
Programming by chat: A large-scale behavioral analysis of 11,579 real-world AI-assisted ide sessions. ASE 2026
Ningzhi Tang, Chaoran Chen, Zihan Fang, Gelei Xu, Maria Dhakal, Yiyu Shi, Collin McMillan, Yu Huang, Toby Jia-Jun Li
[PDF]
Novices Comprehending Functional vs. Imperative Programs: An Eye-Tracking Study. TOSEM
Zihan Fang, Weizhe Jiao, Robert Tairas, Yu Huang
[PDF]
Stop the Retrieval Thrash: Brain-Guided Episodic Memory for Repository-Scale Coding Agents. FSE Companion 2026
Yueke Zhang, Zihan Fang, Kevin Leach
[PDF]
ScanCoder: Leveraging Human Attention Patterns to Enhance LLMs for Code. FSE 2026
Yueke Zhang, Yifan Zhang, Zihan Fang, Greg Trafton, Daniel Levin, Kevin Leach, Yu Huang
[PDF]
Locating Software Vulnerabilities With Static Analyzers: How Far Are We? EASE 2026
Yueke Zhang, Zihan Fang, Kevin Leach, Yu Huang
[PDF]
Investigating the Feasibility of Conducting Webcam-Based Eye-Tracking Studies in Code Comprehension. TSE
Zihan Fang, Robert Wallace, Zachary Karas, Toby Li, Collin McMillan, Yu Huang
[PDF]
Contribution Patterns in Open Source Software for Social Good: Dynamics, Individuals, and Impact. CSCW 2026
Zihan Fang, Yueke Zhang, Thomas Zimmermann, Denae Ford, Yu Huang
[PDF]
CodeACT-R: A Cognitive Simulation Framework for Code Reading. ASE 2025-NIER
Yueke Zhang, Zihan Fang, Greg Trafton, Daniel Levin, Kevin Leach, Yu Huang
[PDF]
A Comparative Study on ChatGPT and Checklist as Support Tools for Unit Testing Education. FSE 2025-SEET
Zihan Fang, Jiliang Li, Anda Liang, Gina R. Bai, Yu Huang
[PDF]
“Math Is a Pain!”: Understanding Challenges and Needs of the Machine Learning Community on Stack Overflow. CSCW 2024
Zihan Fang, Yu Huang
[PDF]
A Four-Year Study of Student Contributions to OSS vs. OSS4SG with a Lightweight Intervention. FSE 2023
Zihan Fang, Madeline Endres, Thomas Zimmermann, Denae Ford, Westley Weimer, Kevin Leach, Yu Huang
🏆 ACM SIGSOFT Distinguished Paper Award [PDF]
Awards
- Ignite Grant at Vanderbilt University
- LIVE Horizon Grant at Vanderbilt University
- C. F. Chen Best Paper Award in the Department of Computer Science at Vanderbilt University
- Richard Bennett/Dorothy Danforth Compton Prize Scholarship at Vanderbilt University
- SIGSOFT Distinguished Paper Award at FSE 2023
- NSF Student Travel Award
Service
- SIGCSE TS 2025 - PC member (Posters)
- SIGCSE TS 2025 - PC member (Computing Education Research)
Experience
- Ph.D. student in Computer Science, Vanderbilt University, Nashville, 2023-2028
- M.S. in Data Science, Vanderbilt University, Nashville, 2021-2023
- B.S. in Information Management, Soochow University, China, 2016-2020