Longxiu Tian studies how consumers respond to marketing activities, particularly when making choices in uncertain environments, to better inform firms’ actions for customer relationship management.
To address these research problems in contemporary CRM contexts and data sources, he develops and applies methods for scalable statistical inference including Bayesian nonparametrics and deep learning for marketing response models, as well as computational techniques including Hamiltonian Monte Carlo, stochastic variational inference and data fusion.
Through his research, he has worked with companies in the areas of consumer credit scoring, online matchmaking and subscription services.
Dr. Tian’s teaching interests include customer relationship management, customer-base analysis and applied econometrics, both at the undergraduate and MBA levels.
Among his previous professional experiences, he was a quantitative researcher in asset management and a research analyst at the Peterson Institute for International Economics.
He received his PhD in marketing and scientific computing from the University of Michigan, his MFin from the MIT Sloan School of Management, and his BA in economics and MS in information systems from Northwestern University.