Michelle Xia

Call for papers: a Special Issue on "Recent Advances in Statistical Machine Learning" (Deadline for submissions: 31 August 2025)

Michelle Xia is an Associate Professor in Statistics at Northern Illinois University (NIU). She served as the Director of Statistical Consulting Services during 2014 to 2019. Michelle obtained her PhD in Statistics from the University of British Columbia, her Master's in Actuarial Science from the University of Calgary, and dual Bachelor's degrees in Insurance and Mathematical Statistics & Probability from Nankai University. 

Besides research, teaching and consulting at NIU, Michelle has over seven years of professional experiences as an actuary, a predictive modeler and a statistician in insurance and medical areas.

Michelle's research is motivated by real life problems, with current interests covering

1. Machine learning including deep learning algorithms for health and insurance data;

2. Statistical methods for complex data including misrepresentation, misclassification and missing information;

3. Predictive analytics, dependence modelling, insurance ratemaking and loss reserving;

4. Bias assessment when using imperfect data, including Bayesian methodological work for partially or weakly identified models;

5. Computational algorithms including Markov chain Monte Carlo (MCMC) and Expectation Maximization (EM) algorithms;

6. Longitudinal and survival methods for complex data.