Research Interests
  • High/Ultra-high dimensional data analysis 
  • Data integration
  • Missing data
  • Application on imaging, -omics, EHRs
  • Bayesian parametric/nonparametric modelling 
Publications
  • Zhao, Y., Zhu, H., Lu, Z., Knickmeyer, R., Zou, F. Structured genome-wide association studies with bayesian hierarchical variable selection. Genetics, in press, 2019.
  • Zhao, Y., Chang, C., Long, Q.. Knowledge-guided statistical learning methods for analysis of high-dimensional -omics data in precision oncology. JCO Precision Oncology, in press, 2019.
  • Zhang X., Chou J., Liang J., Xiao C., Zhao, Y., Sarva H., Henchcliffe C., Wang F.. Data-driven subtyping of parkinson's disease using longitudinal clinical records: a cohort study. Sci Rep 9:797, 2019.
  • Sun, W., Chang, C., Zhao, Y., and Long, Q.. Knowledge-guided Bayesian support vector machine for high-dimensional data with application to genomic Data. IEEE International Conference on Big Data (IEEE BigData 2018), 1484-1493, 2018.
  • Zhang, W., Stephens, C., Blumenfeld, J., Behzadi, A., Donohue, S., Bobb, W., New-house, J., Rennert, H., Zhao, Y., Prince, M.. Relationship of seminal megavesicles, prostate median cysts, and genotype in autosomal dominant polycystic kidney disease. Journal of Magnetic Resonance Imaging, in press, 2018.
  • Chazen, J.L., Cornman-Homonoff, J., Zhao, Y., Sein, M., Feuer, N.. Magnetic resonance neurography of the lumbosacral plexus for lower extremity radiculopathy: frequency of ndings, characteristics of abnormal intraneural signal, and correlation with electromyography. American Journal of Neuroradiology, in press, 2018.
  • Dyke, J.P., Meyring-Wosten, A., Zhao, Y., Linz, P., Thijssen, S., Kotanko, P.. Reliability and agreement of sodium (23NA) MRI in calf muscle and skin of healthy subjects from the US. Clinical Imaging, in press, 2018.
  • Lin, E., Scognamiglio, T., Zhao, Y., Schwartz, T.H., Phillips C.D.. Prognostic implications of gadolinium enhancement of skull base chordomas. American Journal of Neuroradiology, in press, 2018.
  • Acosta, D., Powell, F., Zhao, Y., Raj, A.. Regional vulnerability in Alzheimers disease: the role of cell-autonomous and transneuronal processes. Alzheimer's & Dementia, 14: 797-810, 2018.
  • Kelly, J., Amor-Coarasa, A., Ponnala, S., Nikolopoulou, A., Williams, C., Schlyer, D., Zhao, Y., Kim, D., Babich, J.. Trifunctional PSMA-targeting constructs for prostate cancer with unprecedented localization to LNCaP tumors. European Journal of Nuclear Medicine and Molecular Imaging, 45(11):1841-1851, 2018.
  • Freeze, B., Acosta, D., Pandya, S., Zhao, Y., Raj, A.. Regional expression of genes mediating trans-synaptic alpha-synuclein transfer predicts regional atrophy in Parkinson disease. NeuroImage: Clinical, 28: 456-466, 2018.​
  • Zhang, S., Nguyen, T., Zhao, Y., Gauthier, S., Wang, Y.. Diagnostic accuracy of semiautomatic lesion detection plus quantitative susceptibility mapping in the identi cation of new and enhancing multiple sclerosis lesions. NeuroImage: Clinical, 28(18): 143-148, 2018.
  • Farooq, Z., Behzadi, A., Blumenfeld, J., Zhao, Y., Prince, M.. Measuring liver cyst volumes on MRI or cyst volumes above in autosomal dominant polycystic kidney disease (ADPKD). Clinical Imaging, accepted, 2017.
  • Zhao, Y., Long, Q.. Imputation with high-dimensional data. Wiley StatsRef-Statistics Reference Online, accepted, 2017.
  • Farooq, Z., Behzadi, A., Zhao, Y., Prince, M.. Complex liver cysts in autosomal dominant polycystic kidney disease. Clinical Imaging, in press, 2017.
  • Zhao, Y., Long, Q.. Variable selection in the presence of missing data: imputation-based methods. WIREs Computational Statistics, in press, 2017.
  • Gupta, A., Al-Dasuqi, K., Xia, F., Askin, G., Zhao, Y., Delgodo, D., Wang, Y.. The use of non-contrast quantitative MRI to detect gadolinium-enhancing multiple sclerosis brain lesions: a systematic review and meta-analysis. American Journal of Neuroradiology, 38(7): 1317-1322, 2017.
  • Behzadi, A., Zhao, Y., Farooq, Z., Prince, M.. Immediate reactions to gadolinium based contrast agents: a systematic review and meta-Analysis. Radiology, accepted, 2017.
  • Lan, Z., Zhao, Y., Kang, J., Yu, T.. Bayesian Network Feature Finder (BANFF): an R package for gene network feature selection. Bioinformatics, 32(23): 3685-3687, 2016.
  • Zhao, Y., Chung, M., Johnson, B.A., Moreno, C., Long, Q.. Hierarchical feature selection incorporating known and novel biological information: identifying genomic features related to prostate cancer recurrence. Journal of the American Statistical Association, in press: 2016.
  • Zhao, Y., Long, Q.. Multiple imputation in the presence of high-dimensional data. Statistical Methods in Medical Research, 25(5): 2021-2035, 2016.
  • Zhao, Y., Kang, J., Long, Q.. Bayesian spatial variable selection for ultra-high dimensional neuroimaging data: a multiresolution approach. IEEE/ACM Transactions on Computational Biology and Bioinformatics, in press, 2015.
  • Zhao, Y., Kang, J., Yu, T.. A Bayesian nonparametric mixture model for selecting genes and gene sub-networks. Annals of Applied Statistics, 8(2): 999-1021, 2014.
  • Wasse, H., Huang, R., Long, Q., Zhao, Y., Singapuri, S., Tangpricha, V.. Very high-dose cholecalciferol and arteriovenous stula maturation in ESRD patients: a randomized, double-blind, placebo-controlled pilot study. Journal of Vascular Access, 15 (2): 88-94, 2014.
  • Yu, T., Zhao, Y., Shen, S.. Assessing association between p-value list. Statistical Analysis and Data Mining, 6 (2): 144-155, 2013.
  • Long, Q., Zhang, X., Zhao, Y., Johnson, B.A., Bostick, R.M.. Modeling clinical outcome using multiple correlated functional biomarkers: a Bayesian approach. Statistical Methods in Medical Research, doi: 10.1177/0962280212460444, 2012.
Book Chapter
  • Zhao, Y., Zou, F., Lu, Z., Knickmeyer, R., Zhu, H. (2017). "Bayesian feature selection for ultra-high dimensional imaging genetics data". In: Imaging Genetics, Ed. by A. Dalca, et al.. Elsevier Science.