I am an assistant professor in the Department of Accounting and Information Systems, Broad College of Business, Michigan State University. My research is focused on interpretable learning to achieve a good balance of interpretability and model capacity and applying novel methodology to business analytics.
Methodology: Statistics, machine learning, interpretable learning, Bayesian methods, variational inference, big data.Modeling: Survival analysis, classification, discrete choice models, regression (for skewed and heterogeneous data). Application: Telemedicine, quant marketing, online finance (particularly crowdfunding), medical data analysis, clinical trial
Fall 2020 ITM885 Machine Learning and Optimization
Quan Zhang, Huangjie Zheng and Mingyuan Zhou. "MCMC-Interactive Variational Inference."Quan Zhang, Qiang Gao, Mingfeng Lin and Mingyuan Zhou. "Weibull Racing Time-to-event Modeling and Analysis of Online Borrowers' Loan Payoff and Default."
Quan Zhang and Mingyuan Zhou. "Nonparametric Bayesian Lomax Racing for Survival Analysis with Competing Risks." Advances in Neural Information Processing Systems. 2018. codeQuan Zhang and Mingyuan Zhou. "Permuted and Augmented Stick-Breaking Bayesian Multinomial Regression." Journal of Machine Learning Research (2018): Vol. 18(204) 1−33. Quan Zhang, Youssef Toubouti, and Bradley P. Carlin. "Design and analysis of Bayesian adaptive crossover trials for evaluating contact lens safety and efficacy." Statistical Methods in Medical Research (2017): Vol. 26(3) 1216–1236.