Zilong Zeng

The yEvo Mutation Browser helps students and researchers visualize and interpret genome sequencing data from experimental evolution studies of yeast.

The paper maps personalized functional topography in the neonatal human brain using neuroimaging data and links it to neurocognitive outcomes in early childhood.

The paper analyzes functional and structural MRI data from 33,250 individuals to map lifespan changes in the functional connectome, identifying key developmental stages and differences in neurological disorders.

The paper maps cortical thinning patterns during childhood to adolescence, showing they are structurally constrained by white matter networks and linked to gene expression signatures.

SACNet corrects susceptibility artifacts in dMRI scans using a registration network with neuroanatomical constraints, showing improved performance across diverse datasets.

This paper introduces 3D-MASNet, a 3D mixed-scale asymmetric convolutional network for segmenting infant brain MR images, achieving high Dice coefficients in GM, WM, and CSF.

This paper introduces a deep learning framework to harmonize multisite neuroimaging data by removing site effects while preserving biological features, showing improved performance over traditional methods.