Wen Zhou

Wen Zhou
Associate Professor of Biostatistics
-
Professional overview
-
Wen Zhou is an Associate Professor in the Department of Biostatistics at the School of Global Public Health. He received his Ph.D.s in Statistics and Applied Mathematics from the Iowa State University. His research focuses on developing theories and methods for network data analysis, high-dimensional statistics, multiple testing problems, machine learning, and causal inference. He is particularly interested in applications within genomics, genetics, bioinformatics, protein structure modeling, social science, epidemiology, and health policy. Wen serves on the editorial boards of the Statistica Sinica, Journal of Multivariate Analysis, Biometrics, as well as serves as the Editor-in-Chief of Journal of Biopharmaceutical Statistics. He is an elected member of the International Statistical Institute and has been elected as the WNAR program coordinator in 2024.
Before joining NYU, he was an Associate Professor in Statistics at Colorado State University and held a joint appointment in the Department of Biostatistics and Informatics at the Colorado School of Public Health as well as affiliated to the Molecular, Cellular and Integrative Neurosciences (MCIN) Program.
Visit Dr. Zhou's website to learn more about his professional history and accomplishments.
-
Education
-
BS, Computational Mathematics, Chongqing UniversityPhD, Applied Mathematics, Iowa State UniversityPhD, Statistics, Iowa State University
-
Honors and awards
-
Elected Member of International Statistical Institute (ISI) (2020)NSF junior faculty travel award (2016)Los Alamos Statistical Sciences Conference Grant (2014)5th place finish in the 14th Data Mining Cup Competition (Team leader of the ISU team) (2013)Chair’s Award on Academic Excellence (2012)Graduate Teaching Excellence Award (2010)Robert J. Lambert Award for Excellence in Applied Mathematics (2008)Professional Advancement Grants (2007)
-
Publications
Publications
With random regressors, least squares inference is robust to correlated errors with unknown correlation structure
LARGE-SCALE INFERENCE OF MULTIVARIATE REGRESSION FOR HEAVY-TAILED AND ASYMMETRIC DATA
Ten simple rules for managing laboratory information
Non-asymptotic properties of spectral decomposition of large Gram-type matrices and applications
Tracking the transmission dynamics of COVID-19 with a time-varying coefficient state-space model
A semiparametric latent factor model for large scale temporal data with heteroscedasticity
Large-scale multiple inference of collective dependence with applications to protein function
Nonparallel transcriptional divergence during parallel adaptation
Large scale maximum average power multiple inference on time-course count data with application to RNA-seq analysis
Equilibrium Distributions of Populations of Biological Species on Networks of Social Sites
A single dose polyanhydride-based vaccine platform promotes and maintains anti-GnRH antibody titers
Transcriptome-wide comparison of selenium hyperaccumulator and nonaccumulator Stanleya species provides new insight into key processes mediating the hyperaccumulation syndrome
Transcriptomic analysis of differentially expressed genes in the molting gland (Y-organ) of the blackback land crab, Gecarcinus lateralis, during molt-cycle stage transitions
Comparing large covariance matrices under weak conditions on the dependence structure and its application to gene clustering
On the preservation of cooperation in two-strategy games with nonlocal interactions
Simulation-based hypothesis testing of high dimensional means under covariance heterogeneity
Testing for high-dimensional white noise using maximum cross-correlations
More powerful tests for sparse high-dimensional covariances matrices
Optimality and stability of symmetric evolutionary games with applications in genetic selection
Comparative analyses of C4 and C3 photosynthesis in developing leaves of maize and rice
Quantification of egg yolk contamination in egg white using UV/Vis spectroscopy: Prediction model development and analysis
A computational analysis framework for molecular cell dynamics: Case-study of exocytosis