معرفی
Qiang Wang is an Assistant Professor of Finance at the Haskayne School of Business, University of Calgary. His research bridges financial economics with data science, focusing on FinTech and household finance. He applies computational methods such as natural language processing and topic modeling to analyze complex datasets in both financial and safety-critical domains.
His research interests include FinTech, household finance, cryptocurrency sentiment analysis, decentralized finance (DeFi), and natural language processing. He leverages text analytics and machine learning to extract insights from unstructured data, particularly in financial markets and aviation safety reports.
The recent publications highlight his work in DeFi lending markets and cryptocurrency sentiment. These studies employ advanced data analysis techniques to understand market dynamics, risk factors, and behavioral influences in digital asset ecosystems.
- No scientific awards listed.
There is no public information on students advised or research grants received. However, his interdisciplinary research suggests active collaboration in computational finance and data-driven policy analysis.
His work on aviation safety using Latent Dirichlet Allocation indicates involvement in cross-domain applications of NLP, potentially linked to research teams or labs focused on data science for public safety. His GitHub repository demonstrates technical proficiency and open science practices.
