ABOUT ME

I am currently a Postdoctoral researcher and lecturer in the Software Engineering Research Group (SERG) at the Technical University of Delft. My research is focused on the intersection of natural language processing, source code anaysis, and deep learning. I design and develop learning-based models for automating software engineering and developer-related tasks such as understanding and generating source code, documenting source code, documenting software repositories, and prioritising team tasks.

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. The results of my PhD research were published by several top venues in software engineering community such as Empirical Software Engineering Journal (EMSE), Journal of Systems and Software (JSS), and also SE conferences such as ICSME'21 and SEAA'20. I have a master 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 a motivated and disciplined student looking to contribute to exciting research projects, 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

  • Mar 2022: My tool, Catiss, won the first place in the #NLBSE22 tool competition, co-located with #ICSE22! 🥇 🏆
  • Feb 2022: Our study on evaluation of NLP-based models in SE got accepted to #NLBSE22 workshop, co-located with #ICSE22! 🎉
  • Feb 2022: Our EMSE paper on issue report management got accepted for presentation at #ICSE2022 (Journal First Track). 🎉
  • Dec 2021: Our study with (Dr. Georgios Gousios) on automatic code completion got accepted to #ICSE2022 (Technical Track). 🎉
  • Nov 2021: Our journal first paper on automatic issue management for GitHub repositories got accepted to #EMSE. 🎉
  • Sep 2021: Just started teaching my first BSc class at TU Delft (Software Engineering Methods).
  • Jun 2021: I have started working with the fabulous people of SERG at TU Delft as a Postdoc researcher and lecturer!
  • Jun 2021: Our study on recovering links among software artifacts got accepted to #ICSME21 (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 to #EMSE. 🎉
  • Aug 2020: Our study on generating summaries for methods of event-driven programs got accepted to #JSS. 🎉
  • May 2020: Our paper on improving quality of a post's set of answers got accepted to #SEAA20 (Techncial Track). 🎉
  • Jan 2020: Research visit to the SERG group at TU Delft!

Research Interests

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

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




Publications (listed chronologically)

  1. Izadi, M., CatIss: An Intelligent Tool for Categorizing Issues reports using Transformers, To appear in the Proceedings of the 1sth International Workshop on Natural Language-based Software Engineering (NLBSE), co-located with ICSE, 2022.
  2. Izadi, M., Nili M., On the Evaluation of NLP-based Models for Software Engineering, To appear in the Proceedings of the 1sth International Workshop on Natural Language-based Software Engineering (NLBSE), co-located with ICSE, 2022.
  3. Izadi, M., Gismondi, R., & Gousios G., CodeFill: Multi-token Code Completion by Jointly Learning from Structure and Naming Sequences, To appear in the Proceedings of the 44th IEEE/ACM International Conference on Software Engineering (ICSE), 2022.
  4. Izadi, M., Heydarnoori, A., & Gousios G., Tag Recommendation for Software Repositories using Multi-label Multi-class Classification, Empirical Software Engineering Journal (EMSE), 2022.
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  9. Jalili, M., Ahmadian, S., Izadi, M., Moradi, P., & Salehi, M., Evaluating Collaborative Filtering Recommender Algorithms: A Survey, IEEE Access, 6, 74003-74024. 2018.
  10. 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.
  11. 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.
  12. 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.