
Registered user since Fri 1 May 2020
Dr. Maliheh Izadi is a tenure-track assistant professor in the Faculty of Electrical Engineering, Mathematics, and Computer Science at Delft University of Technology, the Netherlands. She leads the AISE (AI-enabled Sofwater Engineering) research lab at TU Delft. Her work has been supported by various selective funding and awards, including a Google Research Scholar Award (2025) and an Amazon Research Award (2024), as well as industry collaborations such as JetBrains Research. Lastly, she is also the scientific manager for the TU Delft/JetBrains Collaboration, AI4SE.
Maliheh’s research focuses on enhancing software development tools through building smarter software and tailoring machine learning and NLP techniques to source code. Currently, she is working on the challenges of building and tailoring large language models (LLMs) and autonomous agents to source code, such as evaluation, benchmarking, model memorization, IDE integration, in-IDE Human-AI interaction, and extending models’ capabilities to low-resource programming languages.
If you work on similar areas, please consider attending the First International workshop on Autonomous Agents in Software Engineering (AgenticSE) in Seoul, on November 20th, 2025 (co-located with ASE’25).
Contributions
2026
ESEC/FSE
2025
AIware
ASE
- Author of TreeRanker: Fast and Model-agnostic Ranking System for Code Suggestions in IDEs within the Industry Showcase-track
- Author of Evaluating Large Language Models for Functional and Maintainable Code in Industrial Settings: A Case Study at ASML within the Industry Showcase-track
- Author of Prompt-with-Me: in-IDE Structured Prompt Management for LLM-Driven Software Engineering within the Industry Showcase-track
- PC Member in Research Papers within the Research Papers-track
ESEC/FSE
- Author of A Multi-agent Onboarding Assistant based on Large Language Models, Retrieval Augmented Generation, and Chain-of-Thought within the Demonstrations-track
- Session Chair of LLM for SE 3 (part of Research Papers)
- Author of HyperSeq: A Hyper-Adaptive Representation for Predictive Sequencing of States within the Ideas, Visions and Reflections-track
- Committee Member in Program Committee within the Research Papers-track
- Author of Code Red! On the Harmfulness of Applying Off-the-shelf Large Language Models to Programming Tasks within the Research Papers-track
ICSE
NLBSE
- Session Chair of Session 2 - Tool competition (part of Natural Language Based SE)
- Author of Workshop closing within the Natural Language Based SE-track
- Session Chair of Opening (part of Natural Language Based SE)
- Session Chair of Session 1 - Research papers (part of Natural Language Based SE)
- Author of Opening within the Natural Language Based SE-track
Mining Software Repositories
2024
ICSME
ICSE
NLBSE
- Author of Panel Introduction within the NLBSE 2024-track
- Session Chair of Session 1 - Language and code dynamics (part of NLBSE 2024)
- Session Chair of Discussion Panel - Challenges and Opportunities of LLMs (part of NLBSE 2024)
- Session Chair of Opening (part of NLBSE 2024)
- Author of Panel discussion within the NLBSE 2024-track
- Session Chair of Session 2 - Frontiers of collaborative development (part of NLBSE 2024)
Mining Software Repositories
FORGE
- Author of An Exploratory Investigation into Code License Infringements in Large Language Model Training Datasets within the Research Track-track
- Author of Investigating the Performance of Language Models for Completing Code in Functional Programming Languages: a Haskell Case Study within the Research Track-track
2023
Mining Software Repositories
NLBSE
- Author of The (Ab)use of Open Source Code to Train Language Models within the NLBSE 2023-track
- Tool Competition Co-chair of Closing within the NLBSE 2023-track
- Tool Competition Co-chair of Opening & Issue Report Classification Competition within the NLBSE 2023-track
- Tool Competition Co-chair in Organizing Committee within the NLBSE 2023-track
- Author of STACC: Code Comment Classification using Sentence Transformers within the NLBSE 2023-track