Huaxia Li, Ph.D.
Teaching Areas:
BBA AccountingResearch Areas:
Accounting Information Systems, Bond Pricing, Financial AccountingBiography and Education
Huaxia Li is an Assistant Professor of Accounting in the Department of Accounting and Finance at the University of
Michigan-Dearborn. He earned his Ph.D. in Management (Accounting Information Systems) from Rutgers, The State
University of New Jersey. Prior to his current role, he served as a Researcher at the Rutgers Accounting Research Center and
the Continuous Auditing and Reporting Lab.
Education
Ph.D. in Management - Accounting Information Systems, Rutgers, The State University of New Jersey (2025)
Master of Information Technology and Analytics, Rutgers, The State University of New Jersey (2020)
Bachelor of Business Administration in Accounting and Finance, University of Macau (2018)
Teaching and Research
Research
Huaxia’s research interests include accounting information systems, accounting data accessibility, the application of emerging technologies in accounting and auditing, governmental financial accounting and disclosure, municipal bond market and fiscal distress, and corporate social responsibility. He serves on the editorial board of Accounting Open. His work has been published in the Journal of Information Systems, Sustainability Accounting Management and Policy Journal, Journal of Emerging Technologies in Accounting, and International Journal of Disclosure and Governance.
Teaching
Huaxia’s teaching interests include accounting information systems, business data analytics, business automation, and financial, managerial, and governmental accounting. He teaches accounting information systems and business analytics at the University of Michigan-Dearborn.
Selected Publications
Li, H., X. Wang, and H. Issa. 2025. Exploring Mayors’ Disclosure Patterns on Social Media: Evidence from Twitter (X) Expressions. International Journal of Disclosure and Governance, Conditionally Accepted.
Li, H., D. Wei, K. C. Moffitt, and M. A. Vasarhelyi. 2025. Addressing the Last Mile Problem in Open Government Data: Using AIS Technologies to Enhance Governmental Financial Reporting. Journal of Emerging Technologies in Accounting, Forthcoming. https://doi.org/10.2308/JETA-2024-018.
Liu, R., H. Li, K. Yoon, and M. A. Vasarhelyi. 2025. Using Machine Learning Algorithms to Improve Fiscal Distress Prediction Models. Journal of Information Systems, Forthcoming. https://doi.org/10.2308/ISYS-2023-049.
Li, H., H. Gao, C. Wu, and M. A. Vasarhelyi. 2025. Extracting Financial Data from Unstructured Sources: Leveraging Large Language Models. Journal of Information Systems 39 (1): 135–156. https://doi.org/10.2308/ISYS-2023-047.
Li, Q., Z. He, and H. Li. 2024. Uncovering Corporate Greenwashing: A Predictive Model Based on Chinese Heavy-Pollution Industries. Sustainability Accounting, Management and Policy Journal 16 (1): 137–167. https://doi.org/10.1108/SAMPJ-11-2023-0813.
- Li, H., and M. A. Vasarhelyi. 2024. Applying Large Language Models in Accounting: A Comparative Analysis of Different Methodologies and Off-the-Shelf Examples. Journal of Emerging Technologies in Accounting 21 (2): 133–152. https://doi.org/10.2308/JETA-2023-065.
Book Chapter
Li, H. 2025. Exogenous Data in Governmental Accounting: Expanding Auditing Practices. Exogenous Data in Accounting and Auditing in the Rutgers Series in Accounting Information Systems. https://doi.org/10.1108/978-1-83608-734-220251009
Awards and Recognition
American Accounting Association Strategic and Emerging Technologies Research Workshop Best Paper Award (2024)
American Accounting Association Government and Nonprofit Section Midyear Meeting Best Paper Award (2024)
Government Accounting Standard Board Gil Crain Memorial Research Grant (2019)
OpenAI Researcher Access Grant (2024 & 2025)
Stevens Institute of Technology Center for Research toward Advancing Financial Technologies Project, co-sponsored by the National Science Foundation (2025)