Musfiqur Rahman

I am a PhD Candidate in Software Engineering at Concordia University in Montreal, Canada, and a trainee in the CREATE SE4AI program. My research lies at the intersection of Software Engineering and Machine Learning, specifically focusing on building universal, interpretable tools to detect code generated by Large Language Models (LLMs).

Beyond research, I have a background in industry and education, having served as a Lead Data Science Instructor at General Assembly and an AI Engineer at Pentavere. I am a strong advocate for open science, sustainable technology, and education for all.

When I am not coding (usually in Python) or writing, you might find me chasing after my three-year-old. You can also often spot me exploring the streets of Toronto and Montreal, camera in hand. Other times, I’m likely at a cozy café with my beautiful wife, taking a break from the joys and exhaustion of parenting, though we usually end up talking about our little one. If I’m alone, I might be at that same café, daydreaming about a pilgrimage to Mecca or Medina or a future culinary adventure in Japan with my family.

news

Dec 17, 2025	Website is live!

latest posts

Dec 18, 2025	Data Version Control (DVC): The Action and The Reaction
Dec 18, 2025	The Reality Check: Why AI Struggles with Real-World Software Engineering
Dec 17, 2025	Is Code Really More 'Natural' Than English?

selected publications

arXiv

Beyond Synthetic Benchmarks: Evaluating LLM Performance on Real-World Class-Level Code Generation

Musfiqur Rahman, SayedHassan Khatoonabadi, and Emad Shihab

arXiv preprint arXiv:2510.26130, 2025

Bib PDF

@article{rahman2025beyond,
  title = {Beyond Synthetic Benchmarks: Evaluating LLM Performance on Real-World Class-Level Code Generation},
  author = {Rahman, Musfiqur and Khatoonabadi, SayedHassan and Shihab, Emad},
  journal = {arXiv preprint arXiv:2510.26130},
  year = {2025},
}

EASE

The Impact of Environment Configurations on the Stability of AI-Enabled Systems

Musfiqur Rahman, SayedHassan Khatoonabadi, Ahmad Abdellatif, and 2 more authors

In Proceedings of the 29th International Conference on Evaluation and Assessment in Software Engineering, 2025

Bib PDF

@inproceedings{rahman2024impact,
  title = {The Impact of Environment Configurations on the Stability of AI-Enabled Systems},
  author = {Rahman, Musfiqur and Khatoonabadi, SayedHassan and Abdellatif, Ahmad and Samaana, Haya and Shihab, Emad},
  booktitle = {Proceedings of the 29th International Conference on Evaluation and Assessment in Software Engineering},
  year = {2025},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
}

ICSE

Natural Software Revisited

Musfiqur Rahman, Dharani Palani, and Peter C Rigby

In Proceedings of the 41st International Conference on Software Engineering (ICSE), 2019

Bib PDF

@inproceedings{rahman2019natural,
  title = {Natural Software Revisited},
  author = {Rahman, Musfiqur and Palani, Dharani and Rigby, Peter C},
  booktitle = {Proceedings of the 41st International Conference on Software Engineering (ICSE)},
  pages = {37--48},
  year = {2019},
  organization = {IEEE},
}

Other

Using Bayesian networks to model and analyze software product line feature model

Musfiqur Rahman and Shamim Ripon

In Multi-disciplinary Trends in Artificial Intelligence, 2014

Bib PDF

@inproceedings{rahman2014using,
  title = {Using Bayesian networks to model and analyze software product line feature model},
  author = {Rahman, Musfiqur and Ripon, Shamim},
  booktitle = {Multi-disciplinary Trends in Artificial Intelligence},
  pages = {220--231},
  year = {2014},
  organization = {Springer},
}