ABOUT ME

I am an assistant professor in the Software Engineering Research Group (SERG) at Delft University of Technology, the Netherlands. Before that, I was a postdoctoral researcher and lecturer at SERG. My research is at the intersection of natural language processing, source code analysis, and deep learning. I study, design, and develop learning-based models for automating software engineering and developer-related tasks such as understanding, generating, and documenting source code. My work is published by several top venues in the software engineering community such as IEEE/ACM ICSE, MSR, and EMSE.

I hold a PhD in Software Engineering from Sharif University of Technology (SUT), the number one technical university in Iran, advised by Dr. Heydarnoori. My PhD research focused on mining information from version control systems to facilitate software production-related tasks through automatically generating reports (such as release notes) for developers and software teams. I have a master's degree in IT Engineering from SUT, supervised by Dr. Jalili (currently faculty at RMIT University, Melbourne, Australia). My research focus was on improving evaluation methods of recommender systems which resulted in various publications.

If you are a researcher working on the intersection of NLP/ML and software engineering and you are interested in my work, please feel free to reach out to propose/discuss possible collaborations.

NOTE for students: If you are passionate about improving development tools and software engineering processes using large language models for code and would like to work on them, reach out to me for available opportunities. Make sure to introduce yourself, describe your research interests, and enclose a copy of your CV.

Latest News

  • Jun 2023: I have started a new role as an assistant professor at TU Delft, the Netherlands.
  • May 2023: Our tool, STACC, won the first place in the #NLBSE'23 tool competition, co-located with #ICSE'23! 🥇 🏆
  • Mar 2023: Our study on the impact of contextual data on the perfromance of LLM4Code got accepted to the technical track of #MSR'23 conference! 🎉
  • Feb 2023: Our study on the (ab)use of open-source code for training LLM4Code got accpeted to the #NLBSE'23 workshop, co-located with #ICSE'23! 🎉
  • Feb 2023: Our tool won the first place in the #SATML23's LLM's data extraction challenge! 🥇 🏆
  • Jan 2023: Our EMSE paper on semantic-based recommenders got accepted for presentation at #ICSE'23 (Journal First Track). 🎉
  • Dec 2022: Our work on extending LLMs to decompiled code got accepted in the #SANER'23 conference. 🎉
  • Nov 2022: Our study on missing topic recommendation got accepted in the #EMSE journal. 🎉
  • Mar 2022: My tool, Catiss, won the first place in the #NLBSE'22 tool competition, co-located with #ICSE'22! 🥇 🏆
  • Feb 2022: Our study on evaluation of NLP-based models in SE got accepted to #NLBSE'22 workshop, co-located with #ICSE'22! 🎉
  • Feb 2022: Our EMSE paper on issue report management got accepted for presentation at #ICSE'22 (Journal First Track). 🎉
  • Dec 2021: Our study with (Dr. Georgios Gousios) on automatic code completion got accepted to #ICSE'22 (Technical Track). 🎉
  • Nov 2021: Our journal first paper on automatic issue management for GitHub repositories got accepted in the #EMSE journal. 🎉
  • Sep 2021: Just started teaching my first BSc class at TU Delft (Software Engineering Methods).
  • Jun 2021: I have started working with the SERG team at TU Delft as a Postdoc researcher and lecturer!
  • Jun 2021: Our study on recovering links among software artifacts got accepted to #ICSME'21 (Technical Track). 🎉
  • May 2021: I successfully finished my PhD at Sharif University of Technology! ‍
  • May 2021: All four of my MSc students successfully graduated with perfect scores (I was their daily supervisor for the past two years). 💪
  • Apr 2021: Our journal first paper on automatic topic recommednation for GitHub repositories got accepted in the #EMSE journal. 🎉
  • Aug 2020: Our study on generating summaries for methods of event-driven programs got accepted in the #JSS journal. 🎉
  • May 2020: Our paper on improving quality of a post's set of answers got accepted to #SEAA'20 (Techncial Track). 🎉

Research Interests

  • Applied machine learning and deep learning
  • Recommender systems
  • Software Analytics
  • Source Code Analysis
  • Natural language processing

For a copy of my CV, feel free to send me an email.



Publications (listed chronologically)

  1. van Dam, T., Izadi M., & van Deursen, A., Enriching Source Code with Contextual Data for Code Completion Models: An Empirical Study, To appear in the 20th IEEE Working Conference on Mining Software Repositories (MSR), technical track, 2023.
  2. Al-Kaswan, A. & Izadi M., The (Ab) use of Open Source Code to Train Large Language Models, To appear in the Proceedings of the 2nd International Workshop on Natural Language-based Software Engineering (NLBSE), co-located with ICSE, 2023.
  3. Al-Kaswan, A., Izadi M., & van Deursen, A., STACC: Code Comment Classification using SentenceTransformers, To appear in the Proceedings of the 2nd International Workshop on Natural Language-based Software Engineering (NLBSE), co-located with ICSE, 2023.
  4. Al-Kaswan, A., Izadi M., & van Deursen, A., Targeted Attack on GPT-Neo for the SATML Language Model Data Extraction Challenge, Data extraction competition co-located with (SatML), North Carolina, 2023.
  5. Al-Kaswan, A., Ahmed, T., Izadi M., Sawant, A., Devanbu, P., & van Deursen, A., Extending Source Code Pre-Trained Language Models to Summarise Decompiled Binaries, To appear in the proceedings of the IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER), 2023.
  6. Izadi M., Nejati, M., & Heydarnoori A., Semantically-enhanced Topic Recommendation System for Software Projects, To be published by the Empirical Software Engineering Journal (EMSE), 2022.
  7. Izadi, M., Mazrae, P. R., Mens, T., & van Deursen, A., LinkFormer: Automatic Contextualised Link Recovery of Software Artifacts in both Project-based and Transfer Learning Settings, arXiv preprint, 2022.
  8. Izadi, M., CatIss: An Intelligent Tool for Categorizing Issues reports using Transformers, In the Proceedings of the 1st International Workshop on Natural Language-based Software Engineering (NLBSE), co-located with ICSE, 2022.
  9. Izadi, M., Nili M., On the Evaluation of NLP-based Models for Software Engineering, In the Proceedings of 1st International Workshop on Natural Language-based Software Engineering (NLBSE), co-located with ICSE, 2022.
  10. Izadi, M., Gismondi, R., & Gousios G., CodeFill: Multi-token Code Completion by Jointly Learning from Structure and Naming Sequences, In the Proceedings of the 44th IEEE/ACM International Conference on Software Engineering (ICSE), 2022.
  11. Izadi, M., Heydarnoori, A., & Gousios G., Tag Recommendation for Software Repositories using Multi-label Multi-class Classification, Empirical Software Engineering Journal (EMSE), 2022.
  12. Izadi M., Akbari, K., & Heydarnoori A., Predicting the Objective and Priority of Issue Reports for Software Repositories, To appear in Empirical Software Engineering Journal (EMSE), 2021.
  13. Rostami P., Izadi M., & Heydarnoori A., Automated Recovery of Issue-Commit Links Leveraging Both Textual and Non-textual Data, 37th International Conference on Software Maintenance and Evolution (ICSME), Research Track, 2021.
  14. Izadi, M.*, Aghamohammadi, A.*, & Heydarnoori, A., Generating Summaries for Methods of Event-Driven Programs: an Android Case Study, Journal of Systems and Software (JSS), 2020, *co-first authors.
  15. Tavakoli M., Izadi M., & Heydarnoori A., Improving Quality of a Post's Set of Answers in Stack Overflow, Euromicro Conference on Software Engineering and Advanced Applications (SEAA), 2020.
  16. Jalili, M., Ahmadian, S., Izadi, M., Moradi, P., & Salehi, M., Evaluating Collaborative Filtering Recommender Algorithms: A Survey, IEEE Access, 6, 74003-74024. 2018.
  17. Izadi, M., Izadi, M., & Azarsa, B., The Intonation Patterns of English and Persian Sentences: A Contrastive Study, Research Journal of Education (RJE), 3(9), 97-101, 2017.
  18. Javari, A., Izadi, M., & Jalili, M., Recommender Systems for Social Networks Analysis and Mining: Precision versus Diversity, In Complex Systems and Networks (pp. 423-438). Springer, Berlin, Heidelberg, 2016.
  19. Izadi, M., Javari, A., & Jalili, M., Unifying Inconsistent Evaluation Metrics in Recommender Systems, In Proceedings of ACM RecSys Conference, REDD Workshop, Silicon Valley, USA (pp. 1-7), 2014.