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
Arias-Castro, E. and Qiao,
W. (2022). Embedding functional
data: multidimensional scaling and manifold learning. arXiv:
2208.14540.
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.