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.