Assistant Professor
Department of Computer and Data Sciences
Case School of Engineering
Teaching Information
Teaching Schedule
- CSDS 447: Responsible AI Engineering
- CSDS 393/493: Software Engineering
- CSDS 600: Special Topics
Research Information
Research Interests
My research focuses in the intersection of Software Engineering and AI, developing models, verification techniques, and design principles for responsible AI systems. Combining both formal with empirical methods, I aim to ensure algorithmic fairness and safety across end-to-end AI pipeline and LLM-enabled workflows, through analysis of various software abstractions and their real-world implementations.
[For prospective students] I’m seeking multiple self-motivated students (BS, MS and PhD) to join my research group. If you are interested, please email me your CV and unofficial transcripts.
External Appointments
- Distinguished Reviewer for ACM Transactions on Software Engineering and Methodology (TOSEM).
- Panelist in the National Science Foundation (NSF) grant proposal review.
- Reviewers of the journals: IEEE Transactions on Software Engineering (TSE), IEEE Software, and Empirical Software Engineering (EMSE), Transactions on Affective Computing (TAC), Information and Software Technology (IST)
- Program Committee Member of IEEE/ACM International Conference on Software Engineering (ICSE 2024-25), The ACM International Conference on the Foundations of Software Engineering (FSE 2026), IEEE/ACM International Conference on Automated Software Engineering (ASE 2023-24)
Publications
- Yining She, Sumon Biswas, Christian Kästner and Eunsuk Kang. FairSense: Long-Term Fairness Analysis of ML-Enabled Systems, In Proceedings of the 47th IEEE/ACM International Conference on Software Engineering (ICSE), 2025.
- David OBrien, Sumon Biswas, Sayem Mohammad Imtiaz, Rabe Abdalkareem, Emad Shihab and Hridesh Rajan. Are Prompt Engineering and TODO Comments Friends or Foes? An Evaluation on GitHub Copilot, In Proceedings of the 46th IEEE/ACM International Conference on Software Engineering (ICSE), 2024.
- Sumon Biswas and Hridesh Rajan. Fairify: Fairness Verification of Neural Networks. In Proceedings of the 45th IEEE/ACM International Conference on Software Engineering (ICSE), 2023.
- Usman Gohar, Sumon Biswas and Hridesh Rajan. Towards Understanding Fairness and its Composition in Ensemble Machine Learning. In Proceedings of the 45th IEEE/ACM International Conference on Software Engineering (ICSE), 2023.
- Biswas, Sumon, Yining She, and Eunsuk Kang. "Towards safe ML-based systems in presence of feedback loops." Proceedings of the International Workshop on Dependability and Trustworthiness of Safety-Critical Systems with Machine Learned Components, FSE 2023. 2023.
- Giang Nguyen, Sumon Biswas and Hridesh Rajan. Fix Fairness, Don’t Ruin Accuracy: Performance Aware Fairness Repair using AutoML. In Proceedings of the 31st ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE), 2023.
- Sumon Biswas, Mohammad Wardat and Hridesh Rajan. 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 Proceedings of The 44th International Conference on Software Engineering (ICSE), 2022.
- David OBrien, Sumon Biswas, Sayem Mohammad Imtiaz, Rabe Abdalkareem, Emad Shihab and Hridesh Rajan. 23 Shades of Technical Debt: An Empirical Study on Machine Learning Software. In Proceedings of the 30th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE), 2022.
- Sumon Biswas and Hridesh Rajan. Fair Preprocessing: Towards Understanding Compositional Fairness of Data Transformers in machine learning Pipelines. In Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE), 2021.
- Sumon Biswas and Hridesh Rajan. Do the machine learning models on a crowd sourced platform exhibit bias? An empirical study on model fairness. In Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE), 2020.
- Sumon Biswas, Md Johirul Islam, Yijia Huang, Hridesh Rajan. Boa Meets Python: A Boa Dataset of Data Science Software in Python Language. In the 16th International Conference on Mining Software Repositories (MSR), 2019.
Education
Post Doc
Carnegie Mellon University
PhD
Computer Science
Iowa State University
MS
Computer Science
Iowa State University
Additional Information
Personal website: https://sumonbis.github.io
Currently, I’m focusing on foundation models and LLMs, with an emphasis on safety and responsible deployment of AI agents and systems. Our lab runs the state-of-the-art AISC2 cluster, comprising five HGX H200 servers featuring 40 NVIDIA H200 GPUs (141GB memory each). If you’re excited to push the frontiers of LLMs, let’s talk.