Research Interests
My research interests lie in statistical methods and applications to big data in a variety of fields, such as biomedical data science (e.g., genetics/genomics, imaging, neurological/neuropsychiatric disorders, and mental health), environmental science (e.g., spatial epidemiology and global warming), and social science (e.g., socioeconomics and behavioral genetics).
Mostly motivated by real-world problems, I am passionate about developing statistical methodologies and theories that produce better estimates and inferences for high-dimensional data, transfer learning, mediation analysis, data integration, missing data, statistical computing, and confounder adjustment.
Featured PUBLICATIONs
Bingxin Zhao et al., Common genetic variation influencing human white matter microstructure (2021). Science, 372 (6548). LINK [Perspective article in Science]
Bingxin Zhao et al., Common variants contribute to intrinsic functional architecture of human brain (2022). Nature Genetics, in press. LINK
Bingxin Zhao et al., Genome-wide association analysis of 19,629 individuals identifies variants influencing regional brain volumes and refines their genetic co-architecture with cognitive and mental health traits (2019). Nature Genetics, 51(11), 1637-1644. LINK
Bingxin Zhao et al., Transcriptome-wide association analysis of brain structures yields insights into pleiotropy with complex neuropsychiatric traits (2021). Nature Communications, 842872. LINK
Bingxin Zhao and Hongtu Zhu, On genetic correlation estimation with summary statistics from genome-wide association studies (2021). Journal of the American Statistical Association, in press. LINK
Bingxin Zhao and Fei Zou, On polygenic risk scores for complex polygenic trait prediction (2021). Biometrics, in press. LINK
Bingxin Zhao, Fei Zou, and Hongtu Zhu, Cross-trait prediction accuracy of summary statistics in genome-wide association studies (2022). Biometrics, in press. LINK
The list of all my research papers can be found on Google Scholar.
Selected Projects
Genetic architecture of human brain white matter
Bingxin Zhao et al., Common genetic variation influencing human white matter microstructure (2021). Science, 372 (6548). LINK
Bingxin Zhao et al., Transcriptome-wide association analysis of brain structures yields insights into pleiotropy with complex neuropsychiatric traits (2021). Nature Communications, 842872. LINK
Bingxin Zhao et al., Large-scale GWAS reveals genetic architecture of brain white matter microstructure and genetic overlap with cognitive and mental health traits (n= 17,706) (2019). Molecular Psychiatry, in press. LINK
High-dimensional statistical problems in GWAS
Bingxin Zhao and Hongtu Zhu, On genetic correlation estimation with summary statistics from genome-wide association studies (2022). Journal of the American Statistical Association, in press. LINK
Bingxin Zhao and Fei Zou, On polygenic risk scores for complex polygenic trait prediction (2022). Biometrics, in press. LINK
Bingxin Zhao, Fei Zou, and Hongtu Zhu, Cross-trait prediction accuracy of summary statistics in genome-wide association studies (2022). Biometrics, in press. LINK
Genetic architecture of human brain structures
Bingxin Zhao et al., Genetic influences on the shape of brain ventricular and subcortical structures (2022). medRxiv, 22279691. LINK
Bingxin Zhao et al., Genome-wide association analysis of 19,629 individuals identifies variants influencing regional brain volumes and refines their genetic co-architecture with cognitive and mental health traits (2019). Nature Genetics, 51(11), 1637-1644. LINK
Bingxin Zhao et al., Heritability of regional brain volumes in large-scale neuroimaging and genetic studies (2019). Cerebral Cortex, 29(7), 2904-2914. LINK
Genetic influences on human brain functional organizations
Multi-organ imaging and genetic analyses across human body systems
Bingxin Zhao et al., Heart-brain connections: phenotypic and genetic insights from 40,000 cardiac and brain magnetic resonance images (2021). medRxiv, 21265779. LINK.
Trans-ancestry analyses in human genetics and genomics
Bingxin Zhao, Xiaochen Yang, and Hongtu Zhu, Estimating trans-ancestry genetic correlation with unbalanced data resources (2022). arXiv:2203.12154. LINK.
Source: Bycroft et al. (2018), Figure 1
Biobank-scale analyses of human health, behavior, and socioeconomics
Zirui Fan et al., and Bingxin Zhao, Mapping sleep's phenotypic and genetic links to the brain and heart: a systematic analysis of multimodal brain and cardiac images in the UK Biobank (2022). medRxiv, 22279719. LINK
Bingxin Zhao et al., An atlas of trait associations with resting-state and task-evoked human brain functional architectures in the UK Biobank (2022). medRxiv, 22271371. LINK
Jinjie Lin and Bingxin Zhao, Born to be managers? Genetic links between risk-taking and the likelihood of holding managerial positions (2021). SSRN, 3830040. LINK
Analysis of block-wise high-dimensional matrices using random matrix theory
Bingxin Zhao, Shurong Zheng, and Hongtu Zhu, On block-wise and reference panel-based estimators for genetic data prediction in high dimensions (2022). arXiv:2203.12003. LINK.
Retinal imaging genetics with transfer learning
Bingxin Zhao et al., Eye-brain connections revealed by multimodal retinal and brain imaging genetics in the UK Biobank (2023). medRxiv, 23286035. LINK.