Author

Hanwen Lin

Duke University

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

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Neuroscience· 1

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Research Focus:benchmarking· 1 Approach:graph neural network· 1 Organism:human· 1 Assay:imaging· 1

Frequent Co-Authors

Alexandra BadeaiD· 1 shared Allen W. SongiD· 1 shared Alzheimer's Disease Neuroimaging Initiative· 1 shared Cristian T. BadeaiD· 1 shared Heather Elizabeth WhitsoniD· 1 shared Ines Poves Acle· 1 shared Kim G. JohnsoniD· 1 shared Paula Méndez de Inza· 1 shared

Activity by Year

2026-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperNeuroscience

Alexandra BadeaORCID

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1 paper

Recent·Most cited

Calibration-Aware and Interpretable Graph Learning for Multi-Cohort Diffusion Connectome Brain-Age Modeling

Alexandra Badea, Ines Poves Acle, Paula Méndez de Inza, Hanwen Lin, Robert J. Anderson, Kim G. Johnson, Heather Elizabeth Whitson, Allen W. Song, Cristian T. Badea, Alzheimer's Disease Neuroimaging Initiative, The HABS-HD Study Team

This paper develops a calibration-aware graph learning framework for brain-age modeling across multiple cohorts, finding that recalibration improves performance but cohort-specific calibration is needed for external application.

bioRxiv · Aug 24, 2026 · PreprintNeuroscience