Publications
For a complete list of publications refer to Zhang's CV or Google Scholar page. Code/Pipelines can be found in his GitHub website.
2025
2024
| W. Dai, Z. Zhang, P. Song, H. Zhang, Y. Zhao [2024]. Heritability and genetic contribution analysis of structural-functional coupling in human brain. Imaging Neuroscience. |
| A. Turnbull, F.V. Lin, Z. Zhang [2024]. Issues of parcellation in the calculation of structure–function coupling. Nature Reviews Neuroscience. |
| Y. Zhang, M. Liu, Z. Zhang, D. Dunson [2024]. Motion-Invariant Variational Auto-Encoding of Brain Structural Connectomes. Imaging Neuroscience. |
| A. Allen, Z. Zhang, A Nobel [2024]. CoCoNest: A Continuous Structural Connectivity-based Nested Parcellation of the Human Cerebral Cortex. Network Neuroscience. |
| W. Consagra, M. Cole, X. Qiu and Z. Zhang [2024]. Continuous and Atlas-free Analysis of Brain Structural Connectivity. Annals of Applied Statistics. |
2023
| A. Roy, Z. Lan, Z. Zhang [2023]. Nonparametric Modeling of Diffusion MRI Signal in Q-Space. Data Science in Science. |
| L. L. Duan, Z. Yuwen, G. Michailidis, Z. Zhang [2023]. Low Tree-Rank Bayesian Vector Autoregression Models. Journal of Machine Learning Research. |
| D. Li, P. Nguyen, Z. Zhang, D. Dunson [2023]. Tree Representations of Brain Structural Connectivity via Persistent Homology. Frontiers in Neuroscience, Brain Imaging Methods. |
| Y. Zhao, C. Chang, J. Zhang, Z. Zhang [2023]. Genetic underpinnings of brain structural connectome for young adults. Journal of the American Statistical Association. |
2022
| Y. Li, G. Mateos, Z. Zhang [2022]. Learning to Model the Relationship Between Brain Structural and Functional Connectomes. IEEE Transactions on Signal and Information Processing over Network. |
| Z. Zhang, Y. Wu, D. Xiong, J. G. Ibrahim, A. Srivastava, H. Zhu. [2022]. LESA: Longitudinal Elastic Shape Analysis of Brain Subcortical Structures. Journal of the American Statistical Association, accepted as a discussion paper. |
| P. Dey, Z. Zhang, D. Dunson. [2022]. Outlier Detection for Multi-Network Data. Bioinformatics. |
| Z. Zhang, B. Saparbayeva. [2022]. Amplitude Mean of Functional Data on S2 and its Accurate Computation. Journal of Mathematical Imaging and Vision. |
| Q. Chen, A. Turnbull, M. Cole, Z. Zhang, F. V. Lin. [2022]. Enhancing Cortical Network-Level participation Coefficient as a Potential Mechanism for Transfer in Cognitive Training in aMCI. NeuroImage. |
| W. Consagra, A. Venkataramana, Z. Zhang. [2022]. Optimized Diffusion Imaging for Brain Structural Connectome Analysis. IEEE Transactions on Medical Imaging, an earlier version won the runner-up award in the paper competition sponsored by the ASA Statistical Methods in Imaging Section. |
2021
| Z. Zhang, J. Gewandter, P. Geha. [2021]. Brain Imaging Biomarkers for Chronic Pain. Frontiers in Neurology. |
| M. Liu Z. Zhang, D. Dunson. [2021]. Graph Auto-Encoding Brain Networks with Applications to Analyzing Large-Scale Brain Imaging Datasets. NeuroImage. 245, 118750. |
| G. Papadogeorgou Z. Zhang, D. Dunson. [2021]. Soft Tensor Regression. Journal of Machine Learning Research. 22, 1-53. |
| L. Wang, Z. Zhang. [2021]. Classification of Longitudinal Brain Networks with an Application to Understanding Superior Aging. Stat. [in press]. |
| M. Cole, K. Murray, E. St-Onge, B. Risk, J. Zhong, G. Schifitto, M. Descoteaux, Z. Zhang. [2021]. Surface-Based Connectivity Integration: An Atlas-Free Approach to Jointly Study Functional and Structural Connectivity. Human Brain Mapping. [in press]. |
| B. Risk, R. Murden, J. Wu, M. Nebel, A. Venkataraman, Z. Zhang, D. Qiu. [2021]. Which Multiband Factor Should You Choose for Your Resting-State fMRI Study? NeuroImage. 234, 117965. |
| Z. Zhang, X. Wang, L. Kong, H. Zhu. [2021]. High-Dimensional Spatial Quantile Function-on-Scalar Regression. Journal of the American Statistical Association. [in press]. |
| L. Wang, F. Lin, M. Cole, Z. Zhang. [2021]. Learning Clique Subgraphs in Structural Brain Network Classification with Application to Crystallized Cognition. NeuroImage. 225, 117493. |
| X. Wang, G. Zhu, J. Rhen, J. Pang, Z. Zhang. [2021]. Vessel Tech: A High-Accuracy Pipeline for Comprehensive Mouse Retinal Vasculature Characterization. Angiogenesis. 24, 7–11. |
2019
| M. Dai, Z. Zhang, A. Srivastava. [2019]. Analyzing Dynamical Brain Functional Connectivity As Trajectories on Space of Covariance Matrices. IEEE Transactions on Medical Imaging. 39.3, 611-620. |
| M. Dai, Z. Zhang, A. Srivastava. [2019]. Discovering Common Change-Point Patterns in Functional Connectivity Across Population. Medical Imaging Analysis. 58, 101532. |
| Z. Zhang G. Allen, H. Zhu, D. Dunson. [2019]. Tensor Network Factorizations: Relationships Between Brain Structural Connectomes and Traits. NeuroImage. 197, 330-343. |
| L. Wang, Z. Zhang, D. Dunson. [2019]. Symmetric Bilinear Regression for Signal Subgraph Estimation. IEEE Transactions on Signal Processing. 67.7, 1929-1940. |
| L. Wang, Z. Zhang, D. Dunson. [2019]. Common and Individual Structure of Brain Networks. Annals of Applied Statistics. 13.1, 85-112. |
| Z. Zhang, E. Klassen, A. Srivastava. [2019]. Robust Comparison of Kernel Densities on Spherical Domains. Sankhya A. 81.1,144-171. |
| Z. Zhang, M. Descoteaux, D. Dunson. [2019]. Nonparametric Bayes Models of Fiber Curves Connecting Brain Regions.. Journal of the American Statistical Association. 114:528, 1505-1517. |
2018
| Z. Zhang, J. Su, H. Le, E. Klassen, A. Srivastava. [2018]. Rate-Invariant Analysis of Covariance Trajectories. Journal of Mathematical Imaging and Vision. 60, 1306-1323. |
| Z. Zhang, M. Descoteaux, J. Zhang, D. Dunson, A. Srivastava, H. Zhu. [2018]. Mapping Population-based Structural Connectome. NeuroImage. 172, 130-145. |
| Z. Zhang, E. Klassen, A. Srivastava. [2018]. Phase-Amplitude Separation and Modeling of Spherical Trajectories. Journal of Computational and Graphical Statistics. 27.1, 85-97. |
2015 and Earlier
| Z. Zhang, D. Pati, A. Srivastava. [2015]. Bayesian Clustering of Shapes of Curves. Journal of Statistical Planning and Inference. 166, 171-186. |
| Z. Zhang, E. Klassen, A. Srivastava. [2013]. Gaussian Blurring-Invariant Comparison of Signals and Images. IEEE Transactions on Image Processing. 22.8, 3145-3157. |
| Z. Zhang, E. Klassen, A. Srivastava, P.K. Turaga, R. Chellappa. [2011]. Blurring-Invariant Riemannian Metrics for Comparing Signals and Images. International Conference on Computer Vision (ICCV). Barcelona, Spain. |