Author

Dina Zemlyanker

Harvard University

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

Biology Disciplines

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Bioengineering· 1 Neuroscience· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Organism:human· 2 Assay:imaging· 2 Approach:statistical model· 2 Approach:deep learning· 1 Research Focus:differential expression· 1 Approach:experimental assay· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

Juan Eugenio IglesiasiD· 2 shared Adam de HavenoniD· 1 shared Alzheimer’s Disease Neuroimaging Initiative· 1 shared Amelia DemopoulosiD· 1 shared Annabel Sorby‐AdamsiD· 1 shared Ava D. FarnaniD· 1 shared Ian P. Johnson· 1 shared Jonathan Williams-RamireziD· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersBioengineering

Juan Eugenio IglesiasORCID

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2 papers

Recent·Most cited

Improving racial fairness in brain age models using style-transfer synthesis

Vittoria Banchieri, Dina Zemlyanker, Juan Eugenio Iglesias, the Alzheimer’s Disease Neuroimaging Initiative

This paper improves racial fairness in brain age models by using synthetic T1 images generated via style-transfer, reducing disparities without requiring race as an input.

bioRxiv · Sep 22, 2026 · PreprintBioengineering

On the accuracy of image registration in portable low-field 3D brain MRI

Juan Eugenio Iglesias, Ian P. Johnson, Jonathan Williams-Ramirez, Dina Zemlyanker, Lin Tian, Karthik Kuduva Gopinath, Mark Olchanyi, Ava D. Farnan, Amelia Demopoulos, Matthew Scott Rosen, Kevin Navin Sheth, Adam de Havenon, William Taylor Kimberly, Annabel Sorby‐Adams, Alzheimer’s Disease Neuroimaging Initiative

This study evaluates image registration accuracy in portable low-field 3D brain MRI, finding that synthesis-based methods perform best despite acquisition artifacts.

bioRxiv · Feb 14, 2026 · PreprintNeuroscience