Xuwei Guo

I am a Software Engineering Ph.D. candidate at Universiti Kebangsaan Malaysia, working at the intersection of applied artificial intelligence, explainable AI, and empirical software engineering.

My research focuses on AI-driven software engineering, especially software effort estimation, story point estimation, and trustworthy machine learning for agile project decision-making. I am interested in how AI models can be made not only accurate, but also reliable, interpretable, and useful in practical software engineering contexts.

My current research is motivated by a practical question: how can AI support software engineering decisions in a way that is not only accurate, but also reliable and understandable? In my doctoral work, I explore this question through agile effort estimation and story point estimation, using machine learning and large language models as the main technical foundation. I also pay attention to reproducible evaluation, data quality, model reliability, and the practical constraints that affect whether an AI-based estimation method can be trusted in real settings.

Before beginning my Ph.D., I received my B.Eng. degree in Software Engineering from Kunming University of Science and Technology in 2023 and my M.Sc. degree in Computer Science from Universiti Kebangsaan Malaysia in 2024.

I am open to academic collaboration and industry-oriented opportunities related to applied AI, trustworthy machine learning, data science, model evaluation, and AI-driven software engineering.

Research Interests

• AI-driven software engineering
• Explainable artificial intelligence
• Story point estimation
• Software effort and cost estimation
• Trustworthy machine learning for software engineering