I am a Postdoctoral Researcher at Institute for Software Research (ISR), Carnegie Mellon University. I am working with Dr. Eunsuk Kang on the safety and fairness of high-assurance AI based software systems. Prior to that, 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 verifying and reasoning algorithmic fairness in machine learning pipeline.
My research interests are in the intersection of Software Engineering (SE), Programming Languages (PL), and Artificial Intelligence (AI). Broadly, I am focusing on SE for AI and engineering AI based software systems for fairness, safety, and robustness. Especially, my works on fairness verification (ICSE'23), causal reasoning (FSE'22), root cause study (FSE'21), and compositional analysis (ICSE'23), have established fairness as a critical non-functional property of AI based software. Some of my recent works also focus on the AI software architecture (ICSE'22) and ML technical debts (FSE'22) in the open source.
My research continues to combine the formal modeling and design of dependable software, and its application in the real-world. Prior to joining CMU, I worked in the NSF TRIPODS Institute D4 (Dependable Data-Driven Discovery) at ISU during my Ph.D. and worked on the dependability of data-driven software. Furthermore, I worked on the Boa compiler and DSL for conducting large scale mining and program analysis. Especially, I built Python language support for Boa to analyze ML programs and Jupyter Notebooks.
Download my curriculum vitae. Feel free to reach out.
Ph.D. in Computer Science, 2022
Iowa State University
M.S. in Computer Science, 2021
Iowa State University
B.S. in Information Technology, 2015
Jahangirnagar University
TOSEM: Serving in the Board of Distinguished Reviewers for ACM Transactions on Software Engineering and Methodology (TOSEM).
TSE: Serving as the reviewer for IEEE Transactions on Software Engineering (TSE).
EMSE: Serving as a reviewer for Springer Journal - Empirical Software Engineering (EMSE).
ICSE'24: Serving as the Program Committee member of Technical Track of ICSE 2024.
ICSE'23: Serving as the Program Committee member of Student Research Competition track of ICSE 2023.
ASE'22: Served as the Program Committee member of Industry Showcase track of ASE 2022.
ASE'22: Served as the Program Committee member of Late Breaking Results track of ASE 2022.
ESEC/FSE'22: Serving as the Program Committee member of Doctoral Symposium track of ESEC/FSE 2022.
OOPSLA'21 AEC: 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.
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.
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.
Web Chair @ Midwest Big Data Summer School: Served in the organizing committee of the Midwest Big Data Summer School 2021 in Ames, IA, United States.
WiDS Ambassador: Served as the WiDS Ambassador (Women in Data Science) to organize and promote ISU event as part of the annual WiDS Worldwide Conference organized by Stanford University.
Panelist @ ESEC/FSE'20: Served the panel discussion of the session on Fairness at ACM ESEC/FSE 2020 in Sacramento, CA.
We study, design, and analyze the DS pipeline architecture consisting stages such as preprocessing, modeling, training, evaluation, etc.
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.
Mining and analyzing data-science repositories can provide insights from historical data.
Dec 2022: | Two papers accepted at ICSE'22 research track. |
Sep 2022: | Joined the Program Committee of ICSE 2024 technical track. |
Aug 2022: | I’ve been invited to serve the Board of Distinguished Reviewers for the Journal TOSEM (ACM Transactions on Software Engineering and Methodology). |
Jun 2022: | Paper accepted in ESEC/FSE'22 research track. |
May 2022: | Presented ICSE'22 paper on Data Science Pipeline in-person at Pittsburgh, PA. |
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: | I’ve been 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. |
Jul 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. |
Jul 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. |
Jul 2020: | Attending ICSE 2020 conference. |
May 2020: | Organizing Mid-West Big Data Summer School. |
This is one of the largest computer science classes taught at Iowa State (~250 class size). I taught it for three semesters. One of the great experience in the course is to supervise many software project teams.
This is also a very large class which I TA’ed for three semesters. Being heavy on the programming practices, I taught problem-solving, live coding, debugging, and testing.