Department of Mathematics and Statistics

Xiaoli Gao
Associate Professor

Xiaoli

Office: Petty 130
Email address: x_gao2@uncg.edu
Personal web page: www.uncg.edu/~x_gao2/
Starting year at UNCG: 2013
Office hours: TR 12:00 noon - 1:50 p.m., and by appointment

Education

Ph.D. in Statistics, University of Iowa (2008)

Teaching

Fall, 2016
  • STA 551-01 LEC (Introduction to Probability), TR 2:00-3:15, Nursing, Moore Building 331
  • STA 667-04 IND (Statistical Consulting)
  • STA 703-01 LEC (Tpcs in High Dmnsnl Data Anlys), TR 3:30-4:45, Petty Building 007
Spring, 2017
  • STA 552-01 LEC (Introduction to Mathematical Statistics), TR 2:00-3:15, Nursing, Moore Building 328
  • STA 565-01 LEC (Analysis of Survival Data), TR 3:30-4:45, Petty Building 224
  • STA 667-04 IND (Statistical Consulting)

Research Interests

Statistics

Selected Recent Publications

  • Gillies, C. E., Gao, X.L., Patel, N.V., Siadat, M.R., Wilson, G.D.(2012). Improved Feature Selection by Incorporating Gene Similarity into the LASSO, 2012 IEEE 12th International Conference on Data Mining Workshops. An extended version is published in International Journal of Knowledge Discovery in Bioinformatics, 3(1), 1-13, DOI: 0.4018/jkdb.2012010101.
  • Wu, Y. and Gao, X.L. (2011).Sieve estimation with bivariate interval censored data, Journal of Statistics, Application and Theory, 5, 37-61.
  • Gao, X.L. and Fang, Y.X. (2011). A note on the generalized degrees of freedom under the L1 loss function. Journal of Statistical Planning and Inference, 141, 677-686.
  • Gao, X.L. and Huang, J. (2010) A Robust Penalized Method for the Analysis of Noisy DNA Copy Number Data. BMC Genomics, 11:517.
  • Gao, X.L. and Huang, J. (2010). Asymptotic analysis of high-dimensional LAD regression with Lasso. Statistica Sinica, 20 1485-1506.

Brief Bio

Dr. Xiaoli Gao received her Ph.D. in Statistics from the University of Iowa in 2008 and joined UNCG in 2013. Her research interests include High-dimensional Data analysis, Shrinkage analysis, Statistical Genetics, Change point and Survival Analysis. More recent papers can be found on her personal webpage.