734-763-6039

Applications:
Behavioral Science, Economics, Finance and Business, Informatics, Social Science
Methodologies:
Artificial Intelligence, Causal Inference, Databases and Data management, Information Theory, Machine Learning, Natural Language Processing, Statistics

Gregory S. Miller

Ernst and Young Professor of Accounting

Ross School of Business

Greg’s research primarily investigates information flow in financial markets and the actions of agents in those markets – both consumers and producers of that information. His approach draws on theory from the social sciences (economics, psychology and sociology) combined with large data sets from diverse sources and a variety of data science approaches. Most projects combine data from across multiple sources, including commercial data bases, experimentally created data and extracting data from sources designed for other uses (commercial media, web scrapping, cellphone data etc.). In addition to a wide range of econometric and statistical methods, his work has included applying machine learning , textual analysis, mining social media, processes for missing data and combining mixed media.