My doctoral research examines how firms adjust their disclosure behaviour in response to regulatory enforcement, macroeconomic uncertainty, and executive governance structures. Drawing on large-scale financial datasets including WRDS (Compustat, CRSP, BoardEx) and LSEG (Eikon, Datastream), I apply econometric methods such as difference-in-differences, instrumental variables, and Benford's Law anomaly detection to investigate corporate transparency and financial reporting quality in capital markets.

Current research interests extend to CEO social capital and its influence on corporate disclosure and climate risk management, and the effect of regulatory changes on disclosure quality.

Upcoming work explores the intersection of corporate governance, information asymmetry, and sustainability disclosure. I am also motivated to incorporate machine learning and natural language processing methods (including text mining and AI-assisted analysis) to expand the scope and scalability of empirical accounting and finance research.