Ningzhi Tang

I am a 2nd-year Ph.D. student in the Department of Computer Science and Engineering at the University of Notre Dame, advised by Prof. Toby Jia-Jun Li in the SaNDwich Lab. I also work closely with Prof. Collin McMillan at Notre Dame and Prof. Yu Huang at Vanderbilt University. Before joining Notre Dame, I received my B.Eng. degree in the same department at Southern University of Science and Technology (SUSTech), where I conducted research on recommender systems under the guidance of Prof. Yuhui Shi.

My research interests converge at the intersection of Human-Computer Interaction (HCI), Software Engineering (SE), and Artificial Intelligence (AI), where I conduct user studies and build interactive tools to understand and improve how humans work with AI in programming tasks. I have published in venues such as VL/HCC, ICSE, and TSE. My research focuses on two directions:

  • Enhancing AI’s understanding of developer state and intent for personalized assistance;
  • Helping developers interpret and refine AI-generated code through structured representations.

I am actively seeking research internship or product team opportunities in the industry for Summer 2026, especially in areas related to AI-powered developer tools. I’m also always open to connecting, so feel free to reach out!

Selected Publications

(* indicates equal contributions)
Exploring Direct Instruction and Summary-Mediated Prompting in LLM-Assisted Code Modification

Ningzhi Tang, Emory Smith, Yu Huang, Collin McMillan, and Toby Jia-Jun Li

VL/HCC 2025

PDF | IEEE Xplore | GitHub | Slides

Programmer Visual Attention During Context-Aware Code Summarization

Robert Wallace, Aakash Bansal, Zachary Karas, Ningzhi Tang, Yu Huang, Toby Jia-Jun Li, Collin McMillan

TSE 2025

PDF | IEEE Xplore | Zenodo

Developer Behaviors in Validating and Repairing LLM-Generated Code Using IDE and Eye Tracking

Ningzhi Tang*, Meng Chen*, Zheng Ning, Aakash Bansal, Yu Huang, Collin McMillan, and Toby Jia-Jun Li

VL/HCC 2024

PDF | IEEE Xplore | Slides

Towards Effective Validation and Integration of LLM-Generated Code

Ningzhi Tang

VL/HCC 2024: Graduate Consortium

PDF | IEEE Xplore | Slides | Poster

CodeGRITS: A Research Toolkit for Developer Behavior and Eye Tracking in IDE

Ningzhi Tang*, Junwen An*, Meng Chen, Aakash Bansal, Yu Huang, Collin McMillan, and Toby Jia-Jun Li

ICSE 2024: Demonstrations

PDF | ACM DL | Website | GitHub | Video | Slides

An Empirical Study of Developer Behaviors for Validating and Repairing AI-Generated Code

Ningzhi Tang*, Meng Chen*, Zheng Ning, Aakash Bansal, Yu Huang, Collin McMillan, and Toby Jia-Jun Li

PLATEAU 2023

PDF | CMU KiltHub

Semi-decentralized Federated Ego Graph Learning for Recommendation

Liang Qu*, Ningzhi Tang*, Ruiqi Zheng, Quoc Viet Hung Nguyen, Zi Huang, Yuhui Shi, and Hongzhi Yin

WWW 2023

PDF | ACM DL

Single-shot Embedding Dimension Search in Recommender System

Liang Qu*, Yonghong Ye*, Ningzhi Tang, Lixin Zhang, Yuhui Shi, and Hongzhi Yin

SIGIR 2022

PDF | ACM DL