Area of research
Cognitive Neuroscience · Signal Processing
Research interest
Research interests include Functional Brain Connectivity Studies, Neural dynamics and brain function, Blind Source Separation Techniques, and Advanced Neuroimaging Techniques and Applications.
Cortical similarities in psychiatric and mood disorders identified in federated VBM analysis via COINSTAC
Automated Interpretation of Clinical Electroencephalograms Using Artificial Intelligence
Revisiting Functional Dysconnectivity: a Review of Three Model Frameworks in Schizophrenia
Deep Learning in Neuroimaging: Promises and challenges
Federated Analysis in COINSTAC Reveals Functional Network Connectivity and Spectral Links to Smoking and Alcohol Consumption in Nearly 2,000 Adolescent Brains
Deep learning encodes robust discriminative neuroimaging representations to outperform standard machine learning
Federated Analysis of Neuroimaging Data: A Review of the Field
Three‐way parallel group independent component analysis: Fusion of spatial and spatiotemporal magnetic resonance imaging data
Decentralized Multisite VBM Analysis During Adolescence Shows Structural Changes Linked to Age, Body Mass Index, and Smoking: a COINSTAC Analysis
Quantitative EEG Biomarkers for Mild Traumatic Brain Injury
Reading the (functional) writing on the (structural) wall: Multimodal fusion of brain structure and function via a deep neural network based translation approach reveals novel impairments in schizophrenia
Spatio-Temporal Dynamics of Intrinsic Networks in Functional Magnetic Imaging Data Using Recurrent Neural Networks
Deep Learning Applications for Predicting Pharmacological Properties of Drugs and Drug Repurposing Using Transcriptomic Data
Impact of autocorrelation on functional connectivity