734-763-6039

Applications:
Behavioral Science, Business Analytics, Computational Linguistics, Economics, Information Systems, Social Sciences
Methodologies:
Artificial Intelligence, Causal Inference, Data Collection Design, Data Quality, Econometrics, Information Theory, Machine Learning, Missing Data and Imputation, Natural Language Processing, Statistical Inference, 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.