Xiang Yin

Xiang Yin is a Researcher at the Department of Computing, Faculty of Engineering, Imperial College London, specializing in Explainable AI (XAI) and Computational Argumentation (CA). His work focuses on Quantitative Bipolar Argumentation Frameworks (QBAFs) and their explainability.

• PhD in Computing, Imperial College London (2021-2025)
• MSc in Computer Technology, Beihang University (2017-2020)
• BSc in Computer Science and Technology, Hebei University of Technology (2013-2017)

His research explores the integration of computational argumentation with AI systems to enhance transparency and interpretability. Key contributions include formal analysis of argumentation frameworks, counterfactual explanations, and attribution-based interpretability methods.

Recent publications highlight his work on applying argumentation theory to large language models, truth-discovery mechanisms, and theoretical advancements in bipolar argumentation systems. These works span knowledge representation, machine learning, and human-AI collaboration frameworks.

Xiang is affiliated with the Computational Logic and Argumentation group (CLArg) and the Argumentation-based Deep Interactive eXplanations (ADIX) project at Imperial College London. Contact: x.yin20@imperial.ac.uk.