About me

I am currently a Ph.D. student candidate (Dec, 2023) at ECE@Purdue. I am supervised by Prof. James Davis.

My research interest is mainly focused on Software engineering for AI (SE4AI). I am also interested in studying machine learning systems, software supply chain security, and trustworthy/responsible AI.

My work adapts methods from studies on traditional software package registries (e.g., NPM, PyPI) to open-source pre-trained AI model (PTM) supply chain. I currently work on developing novel approaches to enhancing multiple aspects of the PTM supply chain , including trustworthiness, reusability, and security.

Here is a list of projects that I am actively working on:

  • Trustworthiness: Anomaly detection for PTM naming and architectural defects.
  • Reusability: PTM recommendation system considering engineering requirements.
  • Security: Defense against Pickle deserialization vulnerabilities in PTMs.

My work has been published at ISSTA’24, ESEM’24, MSR’24, ICSE’23, MSR’23, ESEC/FSE’22, ASE’22, SCORED’22**, and *EMSE.

I am also the leader of Purdue’s Pre-Trained Models in Deep Learning VIP team (previously TensorFlow Model Garden VIP team where we collaborated with Google).


  • July 2024: Our paper “Interoperability in Deep Learning: A User Survey and Failure Analysis of ONNX Model Converters” has been accepted to ISSTA’24 🎉!
  • June 2024: Our paper “Challenges and Practices of Deep Learning Model Reengineering: A Case Study on Computer Vision” has been accepted to EMSE 🎉!
  • June 2024: Our paper “What do we know about Hugging Face? A systematic literature review and quantitative validation of qualitative claims” has been accepted to ESEM’24 🎉!
  • June 2024: I am excited to announce that I will be joining Socket as a Research Intern this Summer and Fall!
  • May 2024: I am invited to give a talk in Research Data Alliance FAIR for Machine Learning task force (FAIR4ML IG). Welcome to my talk on May 21st, 2024!
  • April 2024: Attending MSR and ICSE 2024 in Lisbon, Portugal. I presented our MSR technical paper PeaTMOSS: A Dataset and Initial Analysis of Pre-Trained Models in Open-Source Software.
  • April 2024: I am invited to the Future Leader Summit for Responsible AI by the Michigan Institute for Data Science (MIDAS).
  • April 2024: Previous REU student and collaborator Matt Hyatt receives NSF GRFP and DOD NDSEG fellowships. Big congrats to Matt! 🎉
  • Feb 2024: Our paper PeaTMOSS: A Dataset and Initial Analysis of Pre-Trained Models in Open-Source Software has been accepted to MSR’24.
  • Dec 2023: Passed my Ph.D. preliminary exam! 🎉


I am delighted to mentor and collaborate with the following students: