Several areas that I work on involve measuring the information processing costs of investors, improving the interpretation of numerical data with textual information, and understanding financial information quality. With recent developments in artificial intelligence and large language models, my recent research focuses on how and whether these new technologies help investors process complex financial information better. My research in financial accounting has been widely cited by major media outlets such as the Financial Times, Wall Street Journal, Forbes, and Bloomberg and has been accepted for publication in prestigious academic journals such as the Journal of Accounting Research and the Journal of Accounting and Economics. To view my current research in accounting/finance, you can visit here. This article from Chicago Booth Review collectively discusses my works in generative LLMs, AI, and financial accounting.

Designing how people process information is inherently complex. Oftentimes, it is challenging to find an appropriate tool kit to empirically test theories in financial economics research. In this context, I am also interested in developing these toolkits by myself (and potentially applying them to my accounting/finance research). My research in Natural Language Processing is centered around developing evaluation and classification frameworks using large language models. My research in computational linguistics has been published in top computer science conferences such as ACL. To view my research in natural language processing, please visit here.