Zhen Zhou

Research Fellow
Laboratories for Computational Neuroimaging (LCN)
MGH, Harvard Medical School
[zzhou22@mgh.harvard.edu] [cv]

Currently, I am a Research Fellow working on develop cutting-edge harmonization methods for brain connectivity at the Athinoula A. Martinos Center for Biomedical Imaging, hosted by Dr. Iman Aganj and Dr. Bruce Fischl.

My research focuses on addressing critical challenges in multi-site neuroimaging studies through innovative computational approaches. Previously, as a postdoctoral researcher co-supervised by Dr. Haochang Shou and Dr. Christos Davatzikos at the University of Pennsylvania, I led research on brain aging through multiscale functional connectivity analysis. During my Ph.D., I had the chance to work with Dr. Han Zhang and Dr. Dinggang Shen at UNC-Chapel Hill to develop the BrainNetClass toolbox and pioneered the first infant-dedicated resting-state fMRI analysis pipeline for the Baby Connectome Project.

News

2025.05: Our paper about harmonization of brain structural connectivity through distribution matching is accepted by Human Brain Mapping.
2024.05: I gave a talk about our recent work at the Buckner & LCN joint Lab Meeting at Harvard.
2024: Several papers I contributed during my time in UPenn are accepted by eBioMedicine, Translational Psychiatry, Nature Communications and PNAS.
2023.07: I am excited to join the Laboratories for Computational Neuroimaging (LCN) at MGH as a Research Fellow.
2023: Two papers I contributed during my time in UNC are accepted by eLife and Developmental Cognitive Neuroscience.
2023.01: Our paper about deep clustering survival machines is accepted by ISBI 2023.
2023.02: Our paper about multiscale functional brain aging connectivity patterns is accepted by Neuroimage.
2022.04: Our work on image biomarkers of bipolar and unipolar depression is accepted by IEEE JBHI.
2022.02: I gave an oral talk at SPIE in Medical Imaging 2022 about our work on Harmonization of multi-site functional connectivity measures in tangent space.

Current Research Areas

Advanced Harmonization Methods for Multi-site Neuroimaging.
Translational Neuroimaging for Early Detection of Neurodegenerative Disease.
Deep learning models for Neuroimaging Data Analysis.

Selected Papers

A selection of papers that represent my research interests (* represents co-first authors).

	Harmonization of Structural Brain Connectivity Through Distribution Matching Zhen Zhou et al. Human Brain Mapping [Code]
	Multiscale functional connectivity patterns of the aging brain learned from harmonized rsfMRI data of the multi-cohort iSTAGING study Zhen Zhou et al. Neuroimage [Code]
	A toolbox for brain network construction and classification (BrainNetClass) Zhen Zhou et al. Human Brain Mapping [Code]
	Multi-layer temporal network analysis reveals increasing temporal reachability and spreadability in the first two years of life Zhen Zhou et al. MICCAI 2019
	Harmonization of multi-site functional connectivity measures in tangent space improves brain age prediction. Zhen Zhou et al. SPIE in Medical Imaging 2022
	Divergent and Convergent Imaging Markers Between Bipolar and Unipolar Depression Based on Machine Learning Huifeng Zhang, Zhen Zhou et al. IEEE Journal of Biomedical and Health Informatics (JBHI)
	Classification of type 2 diabetes mellitus with or withoutcognitive impairment from healthy controls using high-orderfunctional connectivity Yuna Chen, Zhen Zhou et al. Human Brain Mapping

Contact

zzhou22 at mgh.harvard.edu by email