Adam Stein


I'm a third year PhD student at the University of Pennsylvania advised by Professor Mayur Naik. Previously, I attended UCLA where I recieved my BS in CS in 2020. My research is supported by the NSF Graduate Research Fellowship Program.

I'm broadly interested in the fields of programming languages and machine learning, and I'm particularly interested in developing methods for interpreting and debugging machine learning models to improve their reliability and trustworthiness. In particular, I am working on the following problems:


Relational Query Synthesis ⨝ Decision Tree Learning . Aaditya Naik, Aalok Thakkar, Adam Stein, Mayur Naik, Rajeev Alur. VLDB 2024.

Faithful Chain-of-Thought Reasoning . Qing Lyu*, Shreya Havaldar*, Adam Stein*, Li Zhang, Delip Rao, Eric Wong, Marianna Apidianaki, Chris Callison-Burch. AACL 2024.

TopEx: Topic-based Explanations for Model Comparison . Shreya Havaldar, Adam Stein, Eric Wong, Lyle Ungar. ICLR (Tiny Papers Track) 2023.

Learning to Select Pivotal Samples for Meta Re-weighting . Yinjun Wu, Adam Stein, Jacob Gardner, Mayur Naik. AAAI 2023. Oral Presentation.

Some Problems with Properties: A Study on Property-Based Testing in Industry . Harrison Goldstein, Joseph W. Cutler, Adam Stein, Benjamin C. Pierce, Andrew Head. HATRA @ SPLASH 2022.


MDB: Interactively Querying Datasets and Models . Aaditya Naik, Adam Stein, Yinjun Wu, Eric Wong, Mayur Naik. arXiv Pre-print.

Rectifying Group Irregularities in Explanations for Distribution Shift . Adam Stein, Yinjun Wu, Eric Wong, Mayur Naik. arXiv Pre-print.


Automatic Detection of Hybrid Human-Machine Text Boundaries . Joseph W. Cutler*, Liam Dugan*, Shreya Havaldar*, Adam Stein*. CIS 520 Course Project.

Weighted Contrastive Learning for Scene Graph Generation. Joint work with Yinjun Wu and Mayur Naik. 2021 Manuscript.


📧 steinad at

🐦 @adamlsteinl

👨‍💻 @adaminsky