Author

Ciprian M. Crainiceanu

Johns Hopkins UniversityORCID 0000-0001-6601-3881Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Neuroscience· 2 Genetic & Genomic Medicine· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Organism:human· 2 Assay:imaging· 2 Approach:statistical model· 2 Research Focus:batch correction / integration· 1 Approach:benchmark study· 1 Approach:deep learning· 1 Research Focus:GWAS / association mapping· 1

Frequent Co-Authors

Andrew LerouxiD· 2 shared Chang‐Le CheniD· 1 shared Charles M. LaymoniD· 1 shared Charles S DeCarliiD· 1 shared Dana TudorascuiD· 1 shared Davneet Singh MinhasiD· 1 shared Debashree RayiD· 1 shared Diptavo DuttaiD· 1 shared

Activity by Year

2022-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 17 mutual co-author links

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2 shared papersNeuroscience

Andrew LerouxORCID

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3 papers

Recent·Most cited

NeurosciencebioRxivPreprintMar 11, 2026

Exploring Links between Brain Image-Derived Phenotypes and Accelerometer-Measured Physical Activity in the UK Biobank

Dongliang Zhang, Andrew Leroux, Ciprian M. Crainiceanu, Martin A. Lindquist

The paper investigates the association between brain image-derived phenotypes and physical activity using UK Biobank data, finding a strong link between PA and functional connectivity with moderate predictive value for cardiometabolic diseases.

DOI 10.64898/2026.03.10.710798

humanimaging

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NeuroscienceMedical Image AnalysisPeer-reviewedAug 9, 2023

MISPEL: A supervised deep learning harmonizationmethod for multi-scanner neuroimaging data

Mahbaneh Eshaghzadeh Torbati, Davneet Singh Minhas, Charles M. Laymon…·Dana Tudorascu

MISPEL is a supervised deep learning method for harmonizing multi-scanner neuroimaging data, outperforming existing methods in reducing scanner-related variability.

24 citations

imagingdeep learning

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Genetic & Genomic MedicineGenetic EpidemiologyPeer-reviewedJan 18, 2022

Genome-wide association studies of 27 accelerometry-derived physical activity measurements identifies novel loci and genetic mechanisms

Guanghao Qi, Diptavo Dutta, Andrew Leroux…·Nilanjan Chatterjee

This study identifies 5 novel genetic loci associated with physical activity using 27 accelerometry-derived phenotypes from 88,411 UK Biobank participants.

31 citations

humanGWAS summary statistics

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