Zhengwu Zhang

Publications

Selected publications are listed below. For a complete list, see my CV or Google Scholar profile. Code and pipelines are available on GitHub.

2026

  1. I.B. Torres Aguilar, Y. Liu, Z. Zhang [2026]. Short-to-Long Functional Connectivity Transfer via Structure-Aware Latent Diffusion. European Conference on Computer Vision (ECCV).
  2. G. Sargent, W.W. Sun, Z. Zhang, Y. Liu [2026]. Prediction-Powered Adaptive Inference with Pretrained AI Models for Contextual Bandits. International Conference on Machine Learning (ICML).
  3. M.R. Cole, Y. Xiang, W. Consagra, A. Srivastava, X. Qiu, Z. Zhang [2026]. ENCORE: Fast Geometric Framework for Aligning Brain Structural Connectivity on Cortical Manifolds. Medical Image Analysis.
  4. S. Gao, Z. Gu, S. Ding, G. Wang, Z. Zhang, H. Zhao, Y. Zhao [2026]. Brain Functional-Structural Gradient Coupling Reflects Development, Behavior and Genetic Influences. Nature Communications.
  5. Z. Zhang, A.H. Liu, Z. Zhang [2026]. BridgeBP: A Toolbox for Bridging Brain Parcellations and Standardizing Structural Connectivity Matrices. Aperture Neuro.
  6. Y. Xiang, M. Cole, Z. Zhang [2026]. Diffeomorphic Cortical Alignment via Direct Warping of Streamline Endpoints. arXiv preprint.
  7. T. Li, X. Wang, M. Cole, Z. Sun, Z. Jiang, X. Qian, S. Gao, T. Luo, M. Descoteaux, J.L. Stein, X. Wang, T.E. Nichols, H. Zhang, Z. Zhang, H. Zhu [2026]. Connectome-based Spatial Statistics Enabling Large-Scale Population Analyses of Human Connectome Across Cohorts. bioRxiv preprint.
  8. Y. Zhang, M. Liu, Z. Zhang [2026]. Attention-Based Variational Framework for Joint and Individual Components Learning with Applications in Brain Network Analysis. arXiv preprint.

2025

  1. A. Ackerman, Z. Zhang, J. Hannig, J. Prothero, J.S. Marron [2025]. Multifaceted Neuroimaging Data Integration via Analysis of Subspaces. Psychometrika.
  2. R. Liu, Z. Zhang, H. Won, S. Marron [2025]. Significance in Scale Space for Hi-C Data. Bioinformatics.
  3. M. Wu, S. Jing, P.T. Yap, Z. Zhang, M. Liu [2025]. Unpaired Volumetric Harmonization of Brain MRI with Conditional Latent Diffusion. Medical Image Analysis.
  4. L. Wang, D. Li, Z. Zhang [2025]. Riemannian Diffusion Kernel-Smoothed Continuous Structural Connectivity on Cortical Surface. Imaging Neuroscience.
  5. Z. Zhang, A. Venkataraman, M. Cole, T. Ye, D. Qiu, F.V. Lin, B.B. Risk [2025]. The Impact of Multiband and In-Plane Acceleration on White Matter Microstructure Analysis. Human Brain Mapping.
  6. W. Consagra, Z. Gu, Z. Zhang [2025]. NeuroPMD: Neural Fields for Density Estimation on Product Manifolds. Journal of Computational and Graphical Statistics.
  7. R. Yuan, M. Cole, J. Gewandter, J. Markman, Z. Zhang, P. Geha [2025]. Clinical Phenotype Matters: Structural and Functional Thalamic Changes in Neuropathic Low-Back Pain. PAIN.
  8. R. Norel, J. Gewandter, Z. Zhang, A. Tahsin, C.G. Abdallah, J. Markman, et al. [2025]. Turning Patients' Open-Ended Narratives of Chronic Pain Into Quantitative Measures: Natural Language Processing Study. JMIR Human Factors.

2024

  1. 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.
  2. A. Turnbull, F.V. Lin, Z. Zhang [2024]. Issues of parcellation in the calculation of structure–function coupling. Nature Reviews Neuroscience.
  3. Y. Zhang, M. Liu, Z. Zhang, D. Dunson [2024]. Motion-Invariant Variational Auto-Encoding of Brain Structural Connectomes. Imaging Neuroscience.
  4. A. Allen, Z. Zhang, A Nobel [2024]. CoCoNest: A Continuous Structural Connectivity-based Nested Parcellation of the Human Cerebral Cortex. Network Neuroscience.
  5. W. Consagra, M. Cole, X. Qiu and Z. Zhang [2024]. Continuous and Atlas-free Analysis of Brain Structural Connectivity. Annals of Applied Statistics.

2023

  1. A. Roy, Z. Lan, Z. Zhang [2023]. Nonparametric Modeling of Diffusion MRI Signal in Q-Space. Data Science in Science.
  2. L. L. Duan, Z. Yuwen, G. Michailidis, Z. Zhang [2023]. Low Tree-Rank Bayesian Vector Autoregression Models. Journal of Machine Learning Research.
  3. D. Li, P. Nguyen, Z. Zhang, D. Dunson [2023]. Tree Representations of Brain Structural Connectivity via Persistent Homology. Frontiers in Neuroscience, Brain Imaging Methods.
  4. 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

  1. 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.
  2. 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 JASA discussion paper
  3. P. Dey, Z. Zhang, D. Dunson. [2022]. Outlier Detection for Multi-Network Data. Bioinformatics.
  4. Z. Zhang, B. Saparbayeva. [2022]. Amplitude Mean of Functional Data on S2 and its Accurate Computation. Journal of Mathematical Imaging and Vision.
  5. 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.
  6. W. Consagra, A. Venkataraman, Z. Zhang. [2022]. Optimized Diffusion Imaging for Brain Structural Connectome Analysis. IEEE Transactions on Medical Imaging Runner-up, ASA Statistical Methods in Imaging Section paper competition

2021

  1. Z. Zhang, J. Gewandter, P. Geha. [2021]. Brain Imaging Biomarkers for Chronic Pain. Frontiers in Neurology.
  2. M. Liu Z. Zhang, D. Dunson. [2021]. Graph Auto-Encoding Brain Networks with Applications to Analyzing Large-Scale Brain Imaging Datasets. NeuroImage. 245, 118750.
  3. G. Papadogeorgou Z. Zhang, D. Dunson. [2021]. Soft Tensor Regression. Journal of Machine Learning Research. 22, 1-53.
  4. L. Wang, Z. Zhang. [2021]. Classification of Longitudinal Brain Networks with an Application to Understanding Superior Aging. Stat.
  5. 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.
  6. 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.
  7. Z. Zhang, X. Wang, L. Kong, H. Zhu. [2021]. High-Dimensional Spatial Quantile Function-on-Scalar Regression. Journal of the American Statistical Association.
  8. 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.
  9. 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

  1. 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.
  2. M. Dai, Z. Zhang, A. Srivastava. [2019]. Discovering Common Change-Point Patterns in Functional Connectivity Across Population. Medical Imaging Analysis. 58, 101532.
  3. Z. Zhang G. Allen, H. Zhu, D. Dunson. [2019]. Tensor Network Factorizations: Relationships Between Brain Structural Connectomes and Traits. NeuroImage. 197, 330-343.
  4. L. Wang, Z. Zhang, D. Dunson. [2019]. Symmetric Bilinear Regression for Signal Subgraph Estimation. IEEE Transactions on Signal Processing. 67.7, 1929-1940.
  5. L. Wang, Z. Zhang, D. Dunson. [2019]. Common and Individual Structure of Brain Networks. Annals of Applied Statistics. 13.1, 85-112.
  6. Z. Zhang, E. Klassen, A. Srivastava. [2019]. Robust Comparison of Kernel Densities on Spherical Domains. Sankhya A. 81.1,144-171.
  7. 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

  1. 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.
  2. Z. Zhang, M. Descoteaux, J. Zhang, D. Dunson, A. Srivastava, H. Zhu. [2018]. Mapping Population-based Structural Connectome. NeuroImage. 172, 130-145.
  3. 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

  1. Z. Zhang, D. Pati, A. Srivastava. [2015]. Bayesian Clustering of Shapes of Curves. Journal of Statistical Planning and Inference. 166, 171-186.
  2. Z. Zhang, E. Klassen, A. Srivastava. [2013]. Gaussian Blurring-Invariant Comparison of Signals and Images. IEEE Transactions on Image Processing. 22.8, 3145-3157.
  3. 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.