Wanli Qiao

 

Associate Professor

Department of Statistics

George Mason University

Fairfax, VA 22030

 

E-mail: wqiao at gmu dot edu

Phone: (703)993-1707

 

Research areas: modern nonparametric statistics, geometric data analysis, machine learning, extreme value theory, and statistical applications in molecular biology.

 

Publications and Manuscripts - Theory and Methodology

o   Qiao, W. (2023). Confidence regions for filamentary structures. arXiv: 2311.17831.

o   Arias-Castro, E. and Qiao, W. (2024+). Embedding functional data. Accepted by the Annals of Statistics.

o   Arias-Castro, E. and Qiao, W. (2022). Clustering by hill-climbing: consistency results. arXiv: 2202.09023.

o   Arias-Castro, E. and Qiao, W. (2023). A unifying view of modal clustering. Information and Inference: A Journal of the IMA, 12(2), 897-920.

o   Arias-Castro, E. and Qiao, W. (2023). Moving up the cluster tree with the gradient flow. SIAM Journal on Mathematics of Data Science, 5(2), 400-421.

o   Arias-Castro, E., Qiao, W. and Zheng, L. (2022). Estimation of the global mode of a density: minimaxity, adaptation, and computational complexity. Electronic Journal of Statistics, 16(1), 2774-2795.

o   Qiao, W. and Shehu. A. (2022). Space partitioning and regression maxima seeking via a mean-shift-inspired algorithm. Electronic Journal of Statistics, 16(2), 5623-5658.

o   Qiao, W. and Polonik, W. (2021). Algorithms for ridge estimation with convergence guarantees. arXiv: 2104.12314.

o   Qiao, W. (2021). Extremes of locally stationary Gaussian and chi fields on manifolds. Stochastic Processes and their Applications, 133, 166-192.

o   Qiao, W. (2021). Asymptotic confidence regions for density ridges. Bernoulli, 27(2) 946-975. Supplement. (local copy)

o   Qiao, W. (2021). Nonparametric estimation of surface integrals on density level sets. Bernoulli, 27(1) 155-191. (local copy)

o   Qiao, W. (2020). Asymptotics and optimal bandwidth selection for nonparametric estimation of density level sets. Electronic Journal of Statistics, 14(1), 302-344. (local copy)

o   Qiao, W. and Polonik, W. (2019). Nonparametric confidence regions for level sets: statistical properties and geometry. Electronic Journal of Statistics, 13(1), 985-1030. (local copy)

o   Qiao, W. and Polonik, W. (2018). Extrema of rescaled locally stationary Gaussian fields on manifolds, Bernoulli, 24(3), 1834-1859. (local copy)

o   Qiao, W. and Polonik, W. (2016). Theoretical analysis of nonparametric filament estimation. The Annals of Statistics, 44(3), 1269-1297. Supplement. (local copy)

 

Publications - Applications

o   Lei, J., Akhter, N., Qiao, W. and Shehu, A. (2020). Reconstruction and Decomposition of High-Dimensional Landscapes via Unsupervised Learning. KDD'20: Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2505-2513.

o   Qiao, W., Akhter, N., Fang, X., Maximova, T., Plaku, E. and Shehu, A. (2018). From mutations to mechanisms and dysfunction via computation and mining of protein energy landscape. BMC Genomics, 19 (Suppl 7) :671.

o   Akhter, N., Lei, J., Qiao, W., and Shehu, A. (2018). Reconstructing and decomposing protein energy landscapes to organize structure spaces and reveal biologically active states. IEEE Intl Conf on Bioinf and Biomed (BIBM), Madrid, Spain 2018. Pg.56-60.

o   Akhter, N., Qiao, W. and Shehu, A. (2018). An energy landscape treatment of decoy selection in template-free protein structure prediction. Computation, 6(2), 39.

o   Qiao, W., Maximova, T., Plaku, E., and Shehu, A. (2017). Statistical analysis of computed energy landscapes to understand dysfunction in pathogenic protein variants. Comput. Struct. Biol. Workshop (CSBW) - ACM BCB Workshops, Boston, MA pg. 679-684.

o   Qiao, W., Maximova, T., Fang, X., Plaku, E., and Shehu, A. (2017). Reconstructing and mining protein energy landscapes to understand disease, In Proc. of IEEE Intl. Conf. on Bioinf. And Biomed. (BIBM), Kansas City, MO, pg. 22-27.