Research Support

My research has been supported by federal agencies (NIH) and Emory University Woodruff Health Sciences Center. Listed below are selected funding that have contributed to my methodological research efforts.


Statistical ICA Methods for Analysis and Integration of Multi-dimensional Data

Funded by: National Institutes of Health (NIMH), R01

Role: PI/PD (with MPI Kang, J.)

Period: 09/25/2014-07/31/2025

This project seeks to develop novel statistical methods for integrating multi-dimensional data (multimodal imaging/genetics/behavior) to enhance understanding of mechanisms and treatment response of mental disorders.


Statistical Methods for Complex, Multi-Dimensional Data from Cross-sectional and Longitudinal Mental Health Studies

Funded by: National Institutes of Health (NIMH), R01

Role: MPI (with MPI Manatunga, A.K. and Peng, L.)

Period: 07/19/2019-04/30/2024

This project seeks to develop statistical methods for analyzing large-scale and multi-dimensional data in mental health studies to more effectively extract relevant information that are predictive of disease and to help understand individual variability in clinical and neurobiological phenotypes. The applications of the proposed methods will generate new knowledge to further the understanding of the mechanism and progression of the PTSD that will lead to improved disease management strategies.


Method Development of Agreement Measures and Applications in Mental Health

Funded by: National Institutes of Health (NIMH), R01

Role: MPI (with MPI Manatunga, A.K. and Peng, L.)

Period: 09/01/2013-08/3/2017

This proposal aims to develop new statistical methods to investigate the alignment between traditional behavior/clinical outcomes and neuroimaging biomarkers and also to assess agreement and calibrate images from multi-center neuroimaging studies.

Statistical methods for group independent component analysis for multi-subject functional magnetic resonance imaging data

Funded by: Emory University Research Committee/ACTSI

PI: Ying Guo

Period: 06/30/2009-06/30/2010

The objective of this grant is to develop new statistical methods for group independent component analysis (ICA) to estimate subject-specific spatial source signals and to establish formal statistical testing framework for between-group comparisons in spatial domain.

Analytic Methods for Determining Multimodal Biomarkers for Parkinson's Disease

Funded by: National Institutes of Health (NIMH), R01

Role: Co-Investigator (PI: F. DuBois Bowman)

Period: 10/01/12-09/30/15

This project is funded as a part of the NINDS Parkinson's Disease Biomarker Program. We are pursuing two avenues that may reveal early-stage PD biomarkers. First, we are combining datasets from different imaging modalities [including neuromelanin magnetic resonance imaging (NM-MRI) of the locus coeruleus and the substantia nigra, chemical shift imaging (CSI), diffusion tensor imaging (DTI), and resting-state functional MRI], cerebrospinal fluid (CSF) analytes, genotype information, and numerous clinical variables and developing new statistical methods to identify multimodal PD biomarkers from these massive datasets. Secondly, we will consider a Kaiser Permanente clinical database with nearly 250,000 subscribers in Georgia and attempt to determine prior diagnoses, lab results, and medication histories that are risk factors for the subsequent development of PD.


Analytic Methods for Functional Neuroimaging Data

Funded by: National Institutes of Health (NIMH), R01

Role: Co-Investigator (PI: F. DuBois Bowman)

Period: 7/15/2007-6/30/2011

The purpose of this grant is to develop novel statistical methods for 1) predicting patterns of distributed neural processing following a treatment intervention, 2) determing the likelihood of response to treatment on an individual basis, using neural processing information, and 3) developing an improved spatio-temporal modeling framework for analyzing functional neuroimaging data to identify prominent functional connections in brain activity and to identify task-related increases (decreases) in brain activity.


Method Development of Agreement Measures and Applications in Mental Health

Funded by: National Institutes of Health (NIMH), R01

Role: Co-PI (PI: A.K. Manatunga)

Period: 04/01/2008-03/31/2012

This proposal is designed to improve analytic methods for mental health research by developing new methodology, incorporating existing methodology and by targeting this effort toward important scientific mental health studies. These developments will directly benefit mental health research, but they are ubiquitous enough to be generally useful contributions to statistical practice.