Xiang-zhen Kong
Assistant Professor at Zhejiang University
Hangzhou City, Zhejiang, China
Summary
👤
Senior🎓
Top SchoolXiang-zhen Kong is an Assistant Professor and brain scientist with 15 years of experience at the intersection of cognitive neuroscience, neuroimaging, and data science. Trained with a Ph.D. in Cognitive Neuroscience and a BS in Computer Science from Beijing Normal University, he combines rigorous experimental research on brain lateralization and imaging genetics with practical machine-learning and data-engineering skills. His work spans academia and research institutes, including a research stint at the Max Planck Institute, and he actively contributes to open-source neuroimaging tooling—most notably improving the Nipype TBSS pipeline to align outputs with FSL and to strengthen testing and example workflows. Based in Hangzhou, he brings a rare blend of domain expertise and software craftsmanship, often making methodological advances that improve reproducibility and comparability across imaging studies. Colleagues value his ability to translate complex neuroimaging pipelines into robust, reusable workflows that accelerate collaborative science.
15 years of coding experience
Doctor of Philosophy (Ph.D.), Cognitive Neuroscience, Doctor of Philosophy (Ph.D.), Cognitive Neuroscience at Beijing Normal University
Chinese, English
Github Skills (11)
nipype10
fs10
workflow-engine10
python10
data-science10
neuroimaging10
brain-imaging10
testing9
dataflow9
dataflow-programming9
big-data7
Programming languages (8)
Github contributions (5)
nipy/nipype
Apr 2011 - Feb 2012
Workflows and interfaces for neuroimaging packages
Role in this project:
Data Scientist
Data ScientistContributions:16 commits in 10 months
Contributions summary:Xiang-zhen primarily contributed to the development and testing of workflows related to neuroimaging data analysis within the Nipype framework, specifically focusing on the TBSS (Tract-Based Spatial Statistics) pipeline. They refactored and modified existing TBSS code, moved and renamed nodes, and created both example and test scripts to validate the functionality. Their contributions included integrating different components of the TBSS pipeline and comparing the results with existing FSL TBSS outputs.
workflowneuroimagingpythondata-scienceworkflow-engine
Conxz/multiBrain
Aug 2017 - Dec 2019
A list of brain imaging datasets with multiple scans per subject. Feel free to update the list via 'pull requests'!
Contributions:38 commits, 3 PRs, 38 pushes in 2 years 4 months
brainsubjectdatasetimagingpull-requests
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