Ganggang Xu
Assistant Professor, Management Science
Research Interests
Model selection and model averaging for regression models; Spatial data analysis; Spatial and temporal point process modelling; Statistical algorithms with business applications
Featured Publications
- Hessellund, K. B.*, Xu, G*., Guan, Y. and Waagepetersen, R. (2021) "Semi-parametric multinomial logistic regression for multivariate point pattern data," Journal of the American Statistical Association, accepted. (*: joint first authors with equal contributions.)
- Xu, G., Wang, M., Bian, J., Burch, T. R., Andrade, S. C., Huang, H., Zhang, J., and Guan, Y. (2020). "Semi-parametric learning of structured temporal point processes." Journal of Machine Learning Research, 21(192), 1-39.
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Xu, G., Waagepetersen, R., and Guan, Y. (2019) "Stochastic quasi-likelihood for case-control point pattern data." Journal of the American Statistical Association, 114, 631-644.
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Xu, G., Shang, Z., and Cheng, G. (2018) "Optimal tuning for divide-and-conquer kernel ridge regression with massive data." ICML 2018.
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Xu, G. and Genton, M.G. (2017) "Tukey g-and-h random fields." Journal of the American Statistical Association, 112, 1236-1249.
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Xu, G. and Huang, J.Z. (2012) "Asymptotic optimality and efficient computation of the leave-subject-out cross-validation." Annals of Statistics, 40, 3003-3030.
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Xu, G. and Wang, S. (2011) "A goodness-of-fit test of logistic regression based on case-control data with measurement errors." 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