MD Anderson Cancer Center - UTHealth
Graduate School of Biomedical Sciences

Dr. Hongtu Zhu

Dr. Hongtu  Zhu

Regular Member

Professor

The University of Texas MD Anderson Cancer Center
Department of Biostatistics

I am leading a biostatistics and imaging genomics analysis lab (BIG-S2=Statistics and Signals).   I have published more than 200 papers in top journals in the field of statistics, biostatistics, biomedical imaging, and public health and I have received seven NSF and NIH grants. I am an elected Fellow of both the American Statistical Association and Institute of Mathematical Statistics. I am serving as Associate Editor for Statistics and its Interface, JASA Theory & Method, JASA Application and Case Studies, Computational Statistics and Data Analysis, NeuroSurgery, Annals of Statistics, Statistics in Biosciences, Journal of Alzheimer’s Disease, and Statistica Sinica.  As a biostatistician, I have made important methodological contributions in five areas of statistical research including latent variable models, missing data problems, neuroinformatics, diagnostic methods, and big-data integration. My research accomplishments in these areas are directly related to three NIH initiatives including Big Data to Knowledge (BD2K) starting from 2012, Brain Research through Advancing Innovative Neurotechnologies (BRAIN) starting from 2013, and Precision Medicine (PM) starting from 2015.

My methodological research had been focused on the development of various models for the analysis of imaging, genetic, biochemical, behavioral, and clinical data and their integration. Such development requires novel methods that explicitly exploit special features, particularly the correlation, smoothness, and low-dimensional structure, of the data space and the model space. It includes:

  • the selection of important predictors (e.g., genetic, or imaging biomarkers),
  • the design of suitable model regularization schemes to improve prediction accuracy and overcome overfitting,
  • the employment of metrics that target the features of the data/model space, and
  • the development of computationally efficient algorithms with scalability.

PubMed

Contact Information

Phone: 832.750.4931

Email: hzhu5@mdanderson.org

Office: MDA FCT4.6012 (Unit 1411)

Education:

Ph.D. - The Chinese University of Hong Kong - 2000

Programs: