Research Interests

Model selection and model averaging for regression models; Spatial data analysis; Spatial and temporal point process modelling; Machine learning algorithms with business applications

Featured Publications

• 1. Xu, G., Waagepetersen, R. and Guan, Y. (2018) "Stochastic Quasi-likelihood for Case-Control Point Pattern Data,"(Supp) Journal of the American Statistical Association, in press.
  2. Xu, G., Shang, Z., and Cheng, G. (2018) "Optimal tuning for divide-and-conquer kernel ridge regression with massive data," ICML 2018.
  3. Xu, G., Genton, M.G. (2017) "Tukey g-and-h random fields,"(Supp) Journal of the American Statistical Association, 112, 1236-1249.
  4. Xu, G., Huang, J.Z. (2012) "Asymptotic optimality and efficient computation of the leave-subject-out cross-validation." (Supp) Annals of Statistics, 40, 3003-3030.
  5. Xu, G. and Wang, S. (2011) "A goodness-of-fit test of logistic regression based on case-control data with measurement errors." (Supp) Biometrika, 98, 877-886.

Teaching and Professional Experience

• Postdoctoral Research Fellow, Institute for Applied Mathematics and Computational Science (IAMCS), Texas A&M University, College Station, 2012-2014
• Assistant Professor, Department of Mathematical Sciences, Binghamton University, State University of New York, 2014-2018

Degrees

• B.S., Statistics, Zhejiang University, Hangzhou, China, 2006
• M.S., Statistics, Texas A&M University, 2008
• Ph.D., Statistics , Texas A&M University, 2011