I am a Ph.D. candidate at Department of Computer Science in Iowa State University. I am also working as a Research Assistant at Laboratory of Software Design. My supervisor is Dr. Hridesh Rajan. For my dissertation, I am working on improving fairness of machine learning models.
My research interests are in the intersection of Software Engineering (SE), Data Science (DS), and Programming Languages (PL). I worked on mining open source repositories and conducted large-scale program analysis using the Boa framework. Especially, I worked on building Python language support for the Boa compiler and analyzing machine learning (ML) programs and Jupyter notebooks. I am interested in empirical SE research using rich source of metadata and code available in GitHub, StackOverflow, Kaggle, and solve SE problems such as bug detection, modularity, program evolution, code comprehension, etc. I am also interested in verification of high-assurance AI components in software.
Currently, I am working in the D4 (Dependable Data-Driven Discovery) project and focusing on increasing the dependability of data science software. Recently, my research highlighted unfairness in real-world ML models where I investigated the societal bias and their mitigation algorithms in data-driven systems.
Download my resumé. I am in the job market in this academic year 2021-22. Feel free to reach out.
Ph.D. in Computer Science, 2022
Iowa State University
B.Sc. in Information Technology, 2015
Reviewer @ TSE: I am serving as the reviewer for IEEE Transactions on Software Engineering (TSE).
Artifact Evaluation Committee @ OOPSLA'21: I am serving in the program committee of artifact track of ACM SIGPLAN conference on Object-Oriented Programming, Systems, Languages & Applications (OOPSLA'21) co-located at SPLASH 2021, Chicago, IL.
Accessibility Chair @ SPLASH'20-21: I am serving the organizing committee of ACM SIGPLAN conference on Systems, Programming, Languages, and Applications (SPLASH 2020 and SPLASH 2021) with OOPSLA, ECOOP and REBASE in Chicago, IL.
Webmaster @ Midwest Big Data Summer School: I served in the organizing committee of the Midwest Big Data Summer School 2021 in Ames, IA, United States.
We used causal reasoning to measure fairness of components and remove them from machine learning pipeline.
We have studied the software engineering concerns of fairness in real-world machine learning models.
This dataset is created by mining 5M Python program snapshots. The code is transformed to AST for static analysis.
|Aug 2021:||Present paper on Fair Preprocessing in ESEC/FSE'21.|
|July 2021:||Awarded ACM SIGSOFT CAPS grant to attend ESEC/FSE'21.|
|Jun 2021:||Artifact accepted for ESEC/FSE'21 paper on Fair Preprocessing.|
|Jun 2021:||Joined the program committee of the artifact track of OOPSLA'21.|
|Jun 2021:||Received publication award from ISU computer science department for publishing in the top-tier venues.|
|July 2020:||Attending ICSE 2021 conference.|
|Apr 2021:||Paper accepted in ESEC/FSE'21 research track.|
|May 2021:||Passed the Ph.D. candidacy exam.|
|Jan 2021:||Selected for Shadow PC for the MSR'21 technical track.|
|Nov 2020:||Attending OOPSLA'21 conference.|
|Nov 2020:||Present paper on ML Fairness in ESEC/FSE'20.|
|July 2020:||Attending ICSE 2020 conference.|
|May 2020:||Organizing Mid-West Big Data Summer School.|