Aiying Zhang

Assistant Professor

University of Virginia

United States

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About

Aiying Zhang is an Assistant Professor at the University of Virginia. Her research primarily focuses on integrated brain connectivity analysis, studying emotion circuit development in adolescence, and exploring neural dynamics in cognitive disorders. Recent articles highlight her work with advanced neural network models and functional connectomes, emphasizing the intersection of brain imaging and cognitive function prediction.

Articles (14)

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2025

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2024

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2024

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2022

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2021

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2020

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2020

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2020

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2020

Collaborators (2)

Yu-Ping Wang

Tulane University

UNITED STATES

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Vince Calhoun

Professor and Director Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS)

Emory University

UNITED STATES

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Aiying Zhang

Research Interests

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Articles (14)

Integrated brain connectivity analysis with fMRI, DTI, and sMRI powered by interpretable graph neural networks

A Bayesian incorporated linear non-Gaussian acyclic model for multiple directed graph estimation to study brain emotion circuit development in adolescence

Altered Hierarchical Gradients of Intrinsic Neural Timescales in Mild Cognitive Impairment and Alzheimer's Disease

Time‐varying dynamic Bayesian network learning for an fMRI study of emotion processing

Detecting abnormal connectivity in schizophrenia via a joint directed acyclic graph estimation model

Functional connectomes incorporating phase synchronization for the characterization and prediction of individual differences

A Latent Gaussian Copula Model for Mixed Data Analysis in Brain Imaging Genetics

Functional connectome fingerprinting: Identifying individuals and predicting cognitive functions via autoencoder

Interpretable Multimodal Fusion Networks Reveal Mechanisms of Brain Cognition

Correlation Guided Graph Learning to Estimate Functional Connectivity Patterns From fMRI Data

Prediction and classification of sleep quality based on phase synchronization related whole-brain dynamic connectivity using resting state fMRI

A GICA-TVGL framework to study sex differences in resting state fMRI dynamic connectivity

Estimating Dynamic Functional Brain Connectivity With a Sparse Hidden Markov Model

Joint Bayesian-Incorporating Estimation of Multiple Gaussian Graphical Models to Study Brain Connectivity Development in Adolescence

Collaborators (2)

Yu-Ping Wang

Vince Calhoun

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