Hongtu Zhu, PhD
Dr. Hongtu Zhu is a professor in the Department of Biostatistics.
He has a broad background in statistics, biostatistics, medical imaging, genetics and computational neuroscience, with specific training and expertise in neuroimaging data analysis and big data integration as well as secondary data analysis on neurodegenerative and neuropsychiatric diseases.
As a graduate student and postdoctoral fellow, he developed various new statistical methods for analyzing genetic, behavioral and clinical data from cross-sectional, longitudinal and family studies, and solved associated statistical issues (e.g., estimation, hypothesis testing).
As a faculty member at Columbia University and New York State Psychiatric Institute, he expanded his research to develop new statistical methods for the analysis of medical imaging data including magnetic resonance images (MRI), DTI, EEG/MEG, Ultra Sound, fMRI and PET.
Honors and AwardsArthur H. Wuehmann Prize
2011, American Academy of Oral and Maxillofacial RadiologyFellow
2011, American Statistical AssociationFellow
2011, Institute of Mathematical StatisticsTravel Award
2006/2005/2004, NSF/IMS/ENARIndustrial Postdoctoral Fellowship
2000, Pacific Institute for the Mathematical ScienceOutstanding Graduate Scholarship
1998, Chinese University of Hong KongOutstanding Dissertation Award
1996, Southeast UniversityPei Jing-Pei Ying Scholarship
1994, Southeast University
Teaching InterestsUniversity of North Carolina at Chapel Hill
Generalized Linear Models and Applications (BIOS 763), 2007-2010, 2012, 2014
Statistical and Mathematical Analysis of Medical Images (BIOS 773), 2011
Regression Models and Applications (BIOS 762), Fall 2014, 2015
Nonparametric Statistics, Fall 2003
Research ActivitiesResearch interests
Neuroimaging Statistics, Structural Equation Models, Statistical Computing, Diagnostic Methods, Statistical Methods for Manifold Data, Missing Data Problem, Variable Selection, Empirical Likelihood, Diffusion Tensor Imaging, Psychiatry, Psychometrics
University of North Carolina at Chapel Hill
2006-2007; 2009-2014: Doctor Examination Committees I and II, Graduate Studies Committee
2007-2009: Doctor Examination Committees I and II, Seminar Committee
2011-2014: Research Council/Conflict of Interest Committee
2004-2006: Research/Postdoctoral Fellow Training Committee
Professional Service Grants Review
National Science Foundation, 2007, 2009, 2010, 2011, 2012, 2013
NIH Challenge grants, 2009
NIH Neurological, Aging and Musculoskeletal Epidemiology Study Section, 2009, 2010
NIH ZRG1 BST-N(90), 2011
NIH NINDS NeuroNEXT program, 2012, 2013
NIH ZRG1 BDCN-L(60)R, 2013
National Sciences and Engineering Research Council of Canada, 2010, 2011
Chile Foudecyt National Research Funding Competition 2010, 2011
CIHR- Methodological Innovations for Neuroimaging Datasets, 2013
CIHR- Secondary Analysis of Neuroimaging Datasets, 2013
2007: Statistics and its Interface
2011: Statistica Sinica
2012: Journal of American Statistical Association
2013: Annals of Statistics
Guest Editor for a special issue on NeuoroImaging analysis in Statistics and its Interface Student Award
Committee: ICSA 2006 Applied Statistics Symposium
International Chinese Statistical Association Board of Directors, 2012-2014
International Conference on Medical Imaging Computing and Computer Assisted
Intervention (MICCAI) 2008, 2009, 2010, 2011, 2012, 2013
IEEE International Symposium on Biomedical Imaging 2013, 2012, 2011, 2010 Neural Information Processing Systems (NIPS) Conference 2010
Society of Imaging Neuroscience Statisticians. Section on Statistics in Imaging in ASA
One of eight founding members of Section on Statistics in Imaging in ASA
Acting Chair 2012-2013 of Section on Statistics in Imaging in ASA
ENAR Education advisory committee: ENAR 2011
ENAR Student Award Committee: 2010-2012
SBSS Student Award Committee: 2012
Emergence of the brain’s default network: Evidence from two-week-old to four-year-old healthy pediatric subjects. Gao, W., Zhu, H., Giovanello, K.S., Smith, J.K., Shen, D., Gilmore, J., & Lin, W (2009). Proceedings of the National Academic Sciences, 106.
Rician Regression Models for Magnetic Resonance Images. Zhu HT, Li YM, Ibrahim, JG, ..., Peterson BS (2009). Journal of the American Statistical Association, 104.
A note on bootstrapping uncertainty of diffusion tensor parameters. Yung Y, Zhu HT, Ibrahim J, Lin WL, and Peterson B.G (2008). IEEE Transactions on Medical Imaging, 27.
Statistical analysis of diffusion tensors in diffusion-weighted magnetic resonance image data (with discussion). Zhu HT, Zhang HP, Ibrahim JG, and Peterson BG (2007). Journal of the American Statistical Association, 102.
Appropriate perturbation and influence measures in local influence. Zhu HT, Ibrahim, JG, Lee SY, and Zhang HP (2007). Annals of Statistics, 35.
PhD, Statistics, Chinese University of Hong Kong, 2000
MSC, Statistics, Southeast University, 1996