Posts tagged Empirical Study
PTM Naming: Why “What’s in a Name” Actually Matters for AI Reuse
- 27 December 2025
I’m thrilled to share some recent work led by Wenxin Jiang, a PhD student at Purdue University. Wenxin is supervised by James C. Davis, and I have had the pleasure of serving as a key external supervisor and PhD committee member on this project as part of my ongoing collaboration with Dr. Davis. This research was recently accepted for publication in Journal of Empirical Software Engineering and it tackles a problem that anyone working in AI has likely grumbled about: how we name our models.
Improving Deep Learning Reproducibility: A Case Study Investigation (2025)
- 06 May 2025
This paper was led by Nadia Ravi and Aditya Goel (Purdue University), working with James C. Davis. I am one of the key leaders of this research project. The work is available as an arXiv preprint (arXiv:2505.03165).
Deep Learning Model Reengineering: Challenges and Practices (EMSE 2024)
- 30 January 2024
This paper was led by Wenxin Jiang (Purdue University, working with James C. Davis), with contributions from Vishnu Banna, Nikhil Vivek, Aditya Goel, and Nicholas Synovic. I am one of the key leaders of this research project. The work appeared in the Empirical Software Engineering journal.
Pre-Trained Model Reuse in Hugging Face: An Empirical Study (ICSE 2023)
- 14 May 2023
This paper was led by Wenxin Jiang, a PhD student at Purdue University working with James C. Davis. I am one of the key leaders of this research project, contributing to the study design, analysis, and framing. The work appeared at ICSE 2023, the flagship conference in software engineering.