Sumon Biswas

Sumon Biswas

Ph.D. Candidate, Research Assistant

Laboratory for Software Design

Department of Computer Science

Iowa State University


About Me

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.

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

    Iowa State University

  • B.Sc. in Information Technology, 2015

    Jahangirnagar University


Laboratory for Software Design, Iowa State University
Research Assistant
May 2018 – Present 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


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.


CAPS Award
Awarded by ACM to attend ESEC/FSE 2021 conference.
Publication Award
Awarded by ISU Computer Science for publication in the top-tier venues.
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 @ 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.

Shadow PC Member @ MSR'21: I 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: I served the panel discussion of the session on Fairness at ACM ESEC/FSE 2020 in Sacramento, CA.

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.

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

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.