Author

Anees Kazi

Harvard UniversityORCID 0000-0003-4528-1670Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Approach:graph neural network· 2 Assay:imaging· 2 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Approach:deep learning· 1 Research Focus:dimensionality reduction· 1 Organism:human· 1

Frequent Co-Authors

Iman AganjiD· 2 shared Adrian Vasile DalcaiD· 1 shared Agata Łabiak· 1 shared Aina Frau‐PascualiD· 1 shared Bruce R. FischliD· 1 shared Chantal PellegriniiD· 1 shared Jocelyn MoraiD· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

7 top collaborators · 12 mutual co-author links

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2 shared papersBioinformatics

Iman AganjORCID

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2 papers

Recent·Most cited

BioinformaticsFrontiers in NeurosciencePeer-reviewedMay 20, 2026

Structural Connectome Analysis using a Graph-based Deep Model for Age and Dementia Prediction

Anees Kazi, Jocelyn Mora, Bruce R. Fischl…·Iman Aganj

The paper predicts age and MMSE scores from brain connectivity graphs using a graph-based deep learning model, showing improved performance over existing methods.

DOI 10.3389/fnins.2026.1786355

humanimaging

𝕏 PostBluesky

NeuroscienceFrontiers in NeurosciencePeer-reviewedFeb 9, 2026

Multimodal Connectivity-based Cortical Segmentation with Graph Neural Networks

Agata Łabiak, Anees Kazi, Chantal Pellegrini…·Iman Aganj

This paper evaluates Graph Neural Networks for brain cortex segmentation using structural MRI and diffusion MRI data, finding GAT models perform competitively with non-graph methods.

2 citations

imaginggraph neural network

𝕏 PostBluesky