• Non-parametric and semi-parametric methods for curve fitting, prediction and clustering for longitudinal or functional data
• Computational methods to likelihood and Bayesian statistical inference
• Statistical inferences of stochastic processes, optimal stochastic controls and their applications in economics and finance

Recent Publications

1. J. Q. Shi, B. Wang, E. J. Will, and R. M. West. Mixed-effects GPFR models with application to dose-response curve prediction. Statistics in Medicine, 2012
2. Taeryon Choi, J.Q. Shi and Bo Wang. A Gaussian process regression approach to single index model. Journal of Nonparametric Statistics 23, 21-36, 2011. (The winning paper of JNPS 2011 Best Paper Award)
3. T. Chen and B. Wang. Bayesian variable selection for Gaussian process regression: application to chemometric calibration of spectrometers. Neurocomputing 73, 2718-2726, 2010.
4. Bo Wang and D.M. Titterington. Variational Bayesian inference for partially observed stochastic dynamical systems. Journal of Physics: conference series, Volume 143, No. 01, 2009
5. J. Q. Shi and Bo Wang. Curve Prediction and Clustering with Mixtures of Gaussian Process Functional Regression Models. Statistics and Computing 18, 267-283, 2008.