About Me

I am a Postdoctoral Researcher at Institute for Software Research (ISR), Carnegie Mellon University. I am working with Dr. Eunsuk Kang on ensuring reliability of safety-critical AI based software systems. I completed my Ph.D. in Computer Science from Iowa State University (ISU) under the supervision of Dr. Hridesh Rajan. For my dissertation, I worked on reasoning and improving algorithmic fairness in machine learning pipeline.


My research interests are in the intersection of Software Engineering (SE), Programming Languages (PL), and Artificial Intelligence (AI). Especially, my research focuses on the SE for AI area. I worked in the D4 (Dependable Data-Driven Discovery) Institute at ISU and focused on the dependability of data-driven software. Especially, my research unraveled several SE aspects, compositional reasoning, and verification of fairness property in real-world ML pipelines.

I also worked on mining open source repositories and conducted large-scale program analysis using the Boa framework. I built Python language support for the Boa compiler and analyzing machine learning (ML) programs and Jupyter Notebooks. I am interested in SE research using rich source of code and metadata available in GitHub, StackOverflow, Kaggle, and solve SE problems such as defect identification, dependability, modularity, software evolution, etc. I am also interested in reasoning and verifying of high-assurance AI components in software.

Download my resumé. Feel free to reach out for any discussion.

  • Software Engineering
  • Programming Languages
  • Artificial Intelligence
  • Ph.D. in Computer Science, 2022

    Iowa State University

  • M.S. in Computer Science, 2020

    Iowa State University

  • B.Sc. in Information Technology, 2015

    Jahangirnagar University


Institute for Software Research, Carnegie Mellon University
Postdoctoral Researcher
May 2022 – Present Pittsburgh, PA, United States
Laboratory for Software Design, Iowa State University
Research Assistant
May 2018 – May 2022 Ames, Iowa, United States
Dept. of Computer Science, Iowa State University
Teaching Assistant
Aug 2016 – May 2018 Ames, Iowa, United States
Lecturer, Computer Science & Engineering
Jan 2016 – Jul 2016 Dhaka
Software Engineering Intern
Aug 2013 – Dec 2013 Dhaka


The Art and Practice of Data Science Pipelines: A Comprehensive Study of Data Science Pipelines In Theory, In-The-Small, and In-The-Large. In 44th International Conference on Software Engineering (ICSE), 2022.
Fair Preprocessing: Towards Understanding Compositional Fairness of Data Transformers in Machine Learning Pipeline. In 29th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE), 2021.
Do the Machine Learning Models on a Crowd Sourced Platform Exhibit Bias? An Empirical Study on Model Fairness. In 28th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE), 2020.
Boa Meets Python: A Boa Dataset of Data Science Software in Python Language. In 16th International Conference on Mining Software Repositories (MSR), 2019.


Research Excellence Award
Awarded by ISU recognizing outstanding research for the Ph.D. dissertation.
CAPS Award
Awarded by ACM to attend ICSE 2022 conference in-person at Pittsburgh, PA.
Publication Award
Awarded by ISU Computer Science Department in consecutive years 2021-22 for publication in the top-tier venues.
CAPS Award
Awarded by ACM to attend ESEC/FSE 2021 conference.
PLMW Scholar @ PLDI
ACM SIG Scholarships, awarded by Programming Language Mentoring Workshop (PLMW) at PLDI'19 (Programming Language Design and Implementation), Phoenix, AZ.
ACM Travel Grant
Awarded to attend Institute for Mathematics & its Applications (IMA) Workshop, University of Minnesota, June 18-29, 2019.
Professional Advancement Grants
Awarded by Graduate and Professional Student Senate (GPSS) at Iowa State University
NST Fellowship
National Science and Technology (NST) Fellowship Awarded by Ministry of Science & Technology, Bangladesh for Research Excellence.


Reviewer @ TOSEM: Serving as a reviewer for ACM Transactions on Software Engineering and Methodology (TOSEM).

PC Member @ ASE'22: Serving as the Program Committee member of Late Breaking Results track of ASE 2022.

Reviewer @ TSE: Serving as the reviewer for IEEE Transactions on Software Engineering (TSE).

PC Member @ ESEC/FSE'22: Serving as the Program Committee member of Doctoral Symposium track of ESEC/FSE 2022.

WiDS Ambassador: Served as the Women in Data Science (WiDS) Ambassador to organize and promote ISU event as part of the annual WiDS Worldwide Conference organized by Stanford University.

Artifact Evaluation Committee @ OOPSLA'21: Served 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: Served 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.

Shadow PC Member @ MSR'21: Served as the shadow program committee member at the International Conference on Mining Software Repositories (MSR 2021), co-located with ICSE'21, Madrid, Spain.

Panelist @ ESEC/FSE'20: Served the panel discussion of the session on Fairness at ACM ESEC/FSE 2020 in Sacramento, CA.

Webmaster @ Midwest Big Data Summer School: Served in the organizing committee of the Midwest Big Data Summer School 2021 in Ames, IA, United States.

Research Projects

Component-level Fairness in Machine Learning Pipeline

Component-level Fairness in Machine Learning Pipeline

We used causal reasoning to measure fairness of components and remove them from machine learning pipeline.

SE Concerns of Fairness in ML Models

SE Concerns of Fairness in ML Models

We have studied the software engineering concerns of fairness in real-world machine learning models.

ML Repo Dataset from GitHub

ML Repo Dataset from GitHub

This dataset is created by mining 5M Python program snapshots. The code is transformed to AST for static analysis.

Large-Scale Mining of Data-Science Software from GitHub

Large-Scale Mining of Data-Science Software from GitHub

Mining and analyzing data-science repositories can provide insights from historical data.

Recent News

May 2022: Joined ISR at Carnegie Mellon University as a Postdoctoral Researcher
May 2022: Received Research Excellence Award from Iowa State University.
Apr 2022: Organized the Women in Data Science (WiDS) event at ISU and served as an ambassador of WiDS Global, Stanford University.
Apr 2022: Defended my Ph.D. thesis “Understanding and Reasoning Fairness in Machine Learning Pipelines”.
Apr 2022: Awarded ACM SIGSOFT CAPS grant to attend ICSE'22 in-person at Pittsburgh.
Mar 2022: Artifact accepted for my ICSE'22 paper on Data Science Pipelines.
Feb 2022: Gave an invited talk at the CREATE SE4AI group organized by Concordia University, Polytechnique Montreal, Queen’s University, and University of Alberta
Dec 2021: Paper accepted at ICSE'22 research track.
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.