Selected publication
Statistical metholody
Sun, H.-X., Chen, S. X. and Qiu, Y.* (2026). Localization Estimator for High-dimensional Tensor Covariance Matrices. Accepted by The Annals of Statistics.
Su, W. and Qiu, Y.* (2026). High-dimensional Clustering and Signal Recovery under Block Signal. Accepted by The Journal of the American Statistical Association.
Su, W., Li, H., Jing, Z., Qiu, Y.* and Chen, S. X. (2026). Physics-guided Statistical Data Fusion for Reconstructing 3D Current Fields of Oceanic Eddies. Accepted by The Journal of the American Statistical Association.
Qiu, J., Chen, S. X. and Qiu, Y. (2026). Optimally Adaptive Test for High-dimensional Hypotheses via Minimax Deficiency. Accepted by The Journal of the American Statistical Association.
Xia, X. and Qiu, Y.* (2026). Multiply Robust Inference of Average Treatment Effects by High-dimensional Empirical Likelihood. Biometrics, 82 ujag149.
Lu, Q., Chen, S. X. and Qiu, Y. (2026). Versatile Differentially Private Learning for General Loss Functions. The Annals of Statistics, 54 692-717.
Kwon, Y., Kim, J. K. and Qiu, Y. (2026). Generalized Entropy Calibration for Analyzing Voluntary Survey Data. Biometrics, 82 ujag041.
Zhang, B., Hu, J., Zhang, Z., Qiu, Y. and Chen, Y. (2026). CHIP: Cost-efficient High-Dimensional Inference for Generalized Linear Models with Subsampling and One-step Polishing. Accepted by The Annals of Applied Statistics.
Kwon, Y., Kim, J. K. and Qiu, Y.* (2025). Debiased Calibration Estimation Using Generalized Entropy in Survey Sampling. The Journal of the American Statistical Association: Theory and Methods, 121 574–584. Code
Sun, B., Yao, Y., Qiu, Y.* and Zhang, K. (2025). A Sample Efficient Conditional Independence Test in the Presence of Discretization. ICML.
Dong, X., Ng, I., Sun, B., Dai, H., Hao, G.-Y. Fan, S., Spirtes, P. Qiu, Y. and Zhang, K. (2025). Permutation-based Rank Test in the Presence of Discretization and Application in Causal Discovery with Mixed Data. ICML.
Sun, B., Yao, Y., Hao, H.-Y., Qiu, Y.* and Zhang, K. (2025). A Conditional Independence Test in the Presence of Discretization. ICLR.
Du, T., Zhang, Y., Su, W., Jing, Z., Chen, Z., Qiu, Y., Zhang, H., Yang, S. and Ma, W. (2025). Three-Dimensional Observations of a Mesoscale Eddy in the Kuroshio Extension Based on Multiple Platforms. Scientific Data, 12 2013.
Hu, H. and Qiu, Y.* (2025). Rank-based Inference for Conditional Independence Graph with Missing Values. Statistical Analysis and Data Mining, 18 e70028.
He, J., Qiu, Y.* and Zhou, H. (2025). Positive-Definite Regularized Estimation for High-Dimensional Covariance on Scalar Regression. Biometrics, 81 ujaf017.
Cho, S., Kim, J. K. and Qiu, Y. (2025). Multiple Bias Calibration for Valid Statistical Inference under Nonignorable Nonresponse. Biometrics, 81 ujaf044.
Qiu, Y.* and Gu, Y. (2025). F Statistics for High-Dimensional Inference of Linear Model. Bernoulli Journal, 31 2434-2458.
Zhang, S., Chen, S. X. and Qiu, Y.* (2025). Mean Tests for High-Dimensional Time Series. Statistica Sinica, 35 171-201.
Qiu, Y.* and Guo, B. (2024). Minimax Detection Boundary and Sharp Optimal Test for Gaussian Graphical Model. Journal of the Royal Statistical Society: Series B, 86 1221-1242.
Lee, H., Qiu, Y.*, Carriquiry, A. and Ommen, D. (2024). Density-based Matching Rule: Optimality, Estimation, and Application in Forensic Problems. The Annals of Applied Statistics, 18 770-793. Code
Wang, H., Qiu, Y.*, Yin, Y., Guo, H., and Liu, P. (2024). Information-incorporated Gene Network Construction with FDR Control. Bioinformatics, 40 btae125. Package
Qiu, Y., Sun, J. and Zhou, X. H. (2024). Unveiling the Unobservable: Causal Inference on Multiple Derived Outcomes. The Journal of the American Statistical Association: Theory and Methods, 119 2178-2189. Code
Chen, S. X., Qiu, Y.* and Zhang, S. (2023). Sharp Optimality for High Dimensional Covariance Testing. The Annals of Statistics, 51 1921-1945. Code
Chen, S. X., Guo, B. and Qiu, Y.* (2023). Testing and Signal Identification for Two-sample High-dimensional Covariances via Multi-level Thresholding. Journal of Econometrics, 235 1337-1354. Code
Hu, H. and Qiu, Y.* (2023). Inference for Nonparanormal Partial Correlation via Regularized Rank-based Nodewise Regression. Biometrics, 79 1173-1186. Code
Vu, T., Xu, Y., Qiu, Y. and Powers, R. (2023). Shifting-corrected Regularized Regression for H NMR Metabolomics Identification. Biostatistics, 24 140-160.
Qiu, Y. and Zhou, X. H. (2022). Inference on Multi-level Brain Connectivities based on fMRI Data. The Journal of the American Statistical Association: Theory and Methods, 117 2268-2282. Code
Qiu, Y., Tao, J. and Zhou, X. H. (2021). Inference for Heterogeneous Treatment Effects for Observational Data with High-Dimensional Covariates. Journal of the Royal Statistical Society: Series B, 83 1016-1043. Code
Li, Y., Xu, Y. and Qiu, Y. (2021). From multivariate to functional data analysis: fundamentals, recent developments, and emerging areas. Journal of Multivariate Analysis, 188 104806.
Xu, Y., Li, Y. and Qiu, Y. (2021). Growth dynamics and heritability for plant high-throughput phenotyping studies using hierarchical functional data analysis. Biometrical Journal, 63 1325-1341.
Qiu, Y. and Zhou, X. H. (2020). Estimating c-Level Partial Correlation Graphs with Application to Brain Imaging. Biostatistics, 21 641-658. Code
Qiu, Y. and Liyanage, J. (2019). Threshold Selection for Covariance Estimation. Biometrics, 75 985-905. Code
Chang, J., Qiu, Y., Yao, Q. and Zou, T. (2018). Confidence regions for entries of a large precision matrix. Journal of Econometrics, 206 57-82. Code
Qiu, Y., Chen, S. and Nettleton, D. (2018). Detecting Rare and Faint Signals via Thresholding Maximum Likelihood Estimators. The Annals of Statistics, 46 895-923.
Qiu, Y. and Chen, S. (2015). Band Width Selection for High-dimensional Covariance Matrix Estimation. The Journal of the American Statistical Association: Theory and Methods, 110 1160-1174. Code and “bandcov” R package
Qiu, Y. and Chen, S. (2012). Test for Bandedness of High-dimensional Covariance Matrices and Bandwidth Estimation. The Annals of Statistics, 40 1285-1314. Matlab code, “bandcov” R package
Plant science
Kenchanmane, R., Zhang, Y., Mahboub, S., Ngu, D., Qiu, Y., Harmon, F., Schnable, J. C. and Roston, R. L. (2024). Rhythmic lipid and gene expression responses to chilling in panicoid grasses. Journal of Experimental Botany, 75 5790-5804.
Guo, X., Qiu, Y.*, Nettleton, D. and Schnable, P. S. (2023). High-Throughput Field Plant Phenotyping: A Self-Supervised Sequential CNN Model to Segment Overlapping Plants, Plant Phenomics, 5 Article ID 0052.
Guo, X., Qiu, Y.*, Nettleton, D., Yeh, C.-T., Zheng, Z., Hey, S. and Schnable, P. S. (2021). KAT4IA: K-Means Assisted Training for Image Analysis of Field-Grown Plant Phenotypes. Plant Phenomics, Article ID 9805489. Code
Admas, J., Qiu, Y.*, Posadas, L., Eskridge, K. and Graef, G. (2021). Phenotypic Trait Extraction of Soybean Plants Using Deep Convolutional Neural Networks with Transfer Learning. Big Data and Information Analytics, 6 26–40. Code
Wang, R., Qiu, Y.*, Zhou, Y. and Schnable, J. (2020). A Comprehensive Pipeline of Image Processing and Functional Growth Analysis for High Throughput Plant Phenotyping. Plant Phenomics, Article ID 7481687. Code
Liang, Z., Qiu, Y. and Schnable, J. (2020). Genome-phenome Wide Association in Maize and Arabidopsis Identifies a Common Molecular and Evolutionary Signature. Molecular Plant, 13 907-922. Code
Adams, J., Qiu, Y., Xu, Y. and Schnable, J. (2020). Plant Segmentation by Supervised Machine Learning Methods. The Plant Phenome Journal, 3. Code
Choudhury, S., Bashyam, S., Qiu, Y., Samal, A. and Awada, T. (2018). Holistic and Component Plant Phenotyping using Temporal Image Sequence. The Plant Methods, 14 Article number: 35.
Liang, Z., Pandey, P., Stoerger, V., Xu, Y., Qiu, Y., Ge, Y. and Schnable, J. (2018). Conventional and Hyperspectral Time-series Imaging of Maize Lines Widely Used in Field Trials. Gigascience, 7 1-11.
Zhang, Y., Ngu, D., Liang, Z., Qiu, Y., Roston, R. and Schnable, J. (2017). Differentially Regulated Ortholog Analysis to Link Gene Regulatory and Phenotypic Divergence Among Panicoid Grasses. The Plant Cell, 29 1938-1951.
COVID-19
Zhu, Y., Gu, J., Qiu, Y. and Chen, S. X. (2023). Estimating COVID-19 Vaccine Efficacy via Dynamic Epidemiological Models–A Study of Ten Countries. The Annals of Applied Statistics.
Zhu, Y., Gu, J., Qiu, Y.* and Chen, S. X. (2023). Real-World COVID-19 Vaccine Protection Rates against Infection in the Delta and Omicron Eras. Research, 6, Article ID 0099.
Gu, J., Chen, S. X., Dong, Q. and Qiu, Y. (2021). The Effect of Population Migration and Wuhan Lockdown on the Control of COVID-19 Based on vSEIdRm Model. Statistical Research, 38 115-127.
Gu, J., Yan, H., Huang, Y., Zhu, Y., Sun, H., Zhang, X., Wang, Y., Qiu, Y.* and Chen, S. X. (2021). Better Strategies for Containing COVID-19 Pandemic–A Study of 25 Countries via a vSIADR Model. Proceedings of the Royal Society A, 477 No. 2248.
Gu, J., Yan, H., Huang, Y., Zhu, Y., Sun, H., Qiu, Y.* and Chen, S. X. (2020). Comparing Containment Measures among Nations by Epidemiological Effects of COVID-19. National Science Review, 7(12) 1847–1851.
Sun, H., Qiu, Y.*, Yan, H., Huang, Y., Zhu, Y. and Chen, S. (2020). Tracking Reproductivity of COVID-19 Epidemic in China with Varying Coefficient SIR Model. Journal of Data Science (with discussions), 18 455-472.
*: corresponding (co-corresponding) author
Complete list at Google Scholar
Manuscript
Zhan, H., Kim, J. K. and Qiu, Y.* (2026). Multi-source Learning for Target Population by High-dimensional Calibration.
Qiu, Y.*, Tao, J. and Xia, X. (2026). Uniform Inference for Local Conditional Quantile Treatment Effect Curve with High-Dimensional Covariates.
Zhu, Y., Wang, H., Chu, H., Qiu, Y. and Chen, Y. (2026). One-shot Collaborative Indirect Treatment Comparisons with Multiple Distributed Single-arm Trials.
Hu, J., Wang, Y., Wang, T., Qiu, Y., Ning, Y. and Chen, Y. (2026). Targeted Learning of Heterogeneous Sources by Informative Feature Sharing.
Qi, Y., Liu, P. and Qiu, Y.* (2026). Integrative Contrastive Spectral Clustering for Multi-Omics Data Analysis.
Hu, W., Zhu, Y., Zhang, B., Schuemie, M., Qiu, Y.* and Chen, Y. (2026). Multi-site Inference of Causal Effect in the Presence of Unmeasured Confounding.
Zhu, Y., Hu, W., Zhang, B., Hripcsak, G., Qiu, Y.* and Chen, Y. (2026). Robust Causal Inference for Observational Data under Residual Bias.
Sun, Y., Chen, S. X. and Qiu, Y.* (2026). Sequential Machine Learning for Data Assimilation with Parameter Estimation via Hierarchical Bayesian Optimization.
Kim, J. K., Kwon, Y. and Qiu, Y. (2026). Bregman Projection for Calibration Estimation in Survey Sampling.
Wang, H., Zhang, B., Suchard, M., Qiu, Y.* and Chen, Y. (2026). A Distributional Calibration Framework for Robust Real-World Evidence Generation.
Li, H., Ding, X., Su, W., Xiao, Z., Yuan, M., Wang, B., Du, T., Jing, Z., Qiu, Y.* and Chen, S. X. (2026). Reconstructing Four-dimensional High-resolution Features of a Mesoscale Eddy with Multi-glider Observations.
Lee, H., Carriquiry, A. and Qiu, Y.* (2026). A General Framework for Source-Matching Decisions Based on Classification Probabilities.
Qi, Y., Qiu, Y. and Liu, P. (2022). Selective Inference Perspective of Score-based Permutation Test for Canonical Correlation Analysis.
Li, J., Qiu, Y. and Li, L. (2020). A Neighborhood-Assisted Hotelling Test for High-Dimensional Means.