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).

News

• 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! 🎉

Mentorship

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

Ph.D.

• Vishal Purohit (ECE@Purdue, Research Intern@AMD Gen AI)
• Purvish Jajal (ECE@Purdue)
• Nicholas Synovic (CS@Loyola University Chicago)
• Jerin Yasmin (CS@Queen’s University)

MSc

• Jason Jones (ECE@Purdue, SE@BotDojo)

Undergraduate

Graduated

• Diego Montes (ECE@Purdue, Flight SE@SpaceX)
• Vishnu Banna (ECE@Purdue, MLEng@Apple)
• Naveen Vivek (ECE@Purdue, SE@AMD)
• Feny Patel (ECE@Purdue, SE@Meta)
• Zach Ghera (CS@Purdue, SE@Google)
• Ananya Singh (CS+DS@Purdue, SE@Google)
• David Li (ECE@Purdue, SE@Google)
• Allen Liu (ECE@Purdue, SE@Amazon)
• Pongpatapee (Dan) Peerapatanapokin (ECE@Purdue, Application Analyst@Cummins)
• Ibrahim Saeed (CS@Purdue, SE@Magnite)
• Shen Kuo (CS@Purdue, Pursuing MSc@Purdue)
• Heesoo Kim (ECE@Purdue, SE intern@Samsung, Pursuing MSc@Purdue)
• Matt Hyatt (CS@Loyola University Chicago)

Current

• Chingwo Cheung (ECE@Purdue, MLEng@CIMS.AI)
• Mingyu Kim (ECE@Purdue)
• Arav Tewari (CS@Purdue)
• Nathaniel Bielanski (ECE@Purdue)
• Bhavesh Pareek (CS@Purdue, SE intern@Amazon)
• Aaryan Srivastava (CS@Purdue)
• Adrien Qi (CS+Math@Purdue, SE intern@Meta)
• Akshath Raghave R (ECE@Purdue)
• Dulani Wijayarathne (ECE@purdue)
• Isaac In (CS@Purdue)
• Yash Mehta (CS@Purdue)
• Shiva Sai Vummaji (CS+DS@Purdue)
• Rohan Sethi (CS@Loyola University Chicago)
• Aryan Indarapu (ECE@UIUC)