Reading the gap between what firms say and what they do.

I am an interdisciplinary researcher working across accounting, business analytics, and artificial intelligence. My research centres on the credibility of corporate ESG disclosure — how sustainability claims can be extracted from multimodal reporting materials, linked to source evidence, and evaluated for consistency, greenwashing risk, and empirical credibility.

I am currently pursuing a Master of Commerce in Business Analytics at the University of New South Wales. I previously earned a Bachelor of Administration (Honours) in Accounting from Hong Kong Baptist University, completed at its Zhuhai campus, Beijing Normal-Hong Kong Baptist University. My undergraduate thesis, supervised by Dr. Man Hung Alvin Cheng, examined the impact of ESG disclosure on corporate investment efficiency. Building on this accounting and ESG research background, I am now extending my work toward computer science and AI-driven sustainability intelligence.

My research interests include ESG disclosure quality, narrative consistency, greenwashing-gap detection, corporate sustainability assurance, and responsible AI for financial and non-financial reporting. Methodologically, I work across panel econometrics, causal inference, machine learning, explainable AI, retrieval-augmented generation, and NLP-based text analysis.

I am currently developing an AI-assisted ESG report extraction and evidence-mapping system, which aims to transform unstructured sustainability reports into structured, traceable, and auditable evidence for downstream textual and empirical analysis.

I am looking for collaborators interested in ESG analytics, responsible AI, financial data science, and corporate disclosure research. My goal is to develop transparent and verifiable tools for evaluating sustainability claims — bridging accounting research, econometric rigor, and modern language-model capabilities.

Curriculum Vitae