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School of Medicine
Peng Huang, Ph.D.
Associate Professor of Oncology
Dr. Huang's research is in non-parametric machine learning methods for the prediction model development using multi-dimensional data. She has developed several image texture feature extraction techniques that have been independently tested in studies of pulmonary nodules, renal masses, hypervascular liver lesions, and pancreatic lesions.
Dr. Huang received the 2015 Johns Hopkins Discovery Award for her work in "Lung Cancer Early Diagnosis Using Biomarkers from Multiple Platforms" where she was the principal investigator.
Dr. Huang holds a joint appointment at department of oncology (School of Medicine) and department of biostatistics (School of Public Heath). She directs the Biostatistics Resource of the In Vivo Cellular and Molecular Imaging Center (ICMIC) and previous funded breast cancer SPORE Biostatistics and Bioinformatics Core. She is a member of Clinical Research Review Committee and Institutional Review Board in the Johns Hopkins School of Medicine. Dr. Huang has served as a scientific reviewer on multiple NIH study sections and Department of Defense Congressionally Directed Medical Research Programs (CDMRP) review panels.
- Associate Professor of Oncology
Centers & Institutes
Research & Publications
Dr. Huang’s research mainly focuses on global assessment of treatment effect when multiple endpoints are evaluated simultaneously. This includes optimal study design with multiple endpoints, sequential clinical trial data monitory, and final data analysis of multiple endpoints. Dr. Huang has received NIH research grant award in the development of global statistical test. She won the 1997 Shewell Award from American Society for Quality Control for her innovative minimum aberration split-plot design which has been adopted into the widely used SAS software.
At Johns Hopkins University, Dr. Huang’s main role is to provide biostatistics support in study design and data analysis. She is a full member of Clinical Research Review Committee at The Sidney Kimmel Comprehensive Cancer Center, the leading biostatistician in breast cancer, liver cancer, and imaging studies. Dr. Huang has extensive experiences in statistical design and data analysis for clinical trials and lab experiments. Outside Johns Hopkins, Dr. Huang serves in multiple NIH/CSR and NIH/NCI study section review panels since 2002. Currently, Dr. Huang is a member of NIH/CSR Clinical Neuroscience and Disease (CNN) Study Section (a six-year appointment).
Huang P, Chen D, Voelkel JO. Minimum aberration two-level split plot design. Technometrics. 1998;40(4):314-326
Huang P. Existence of a minimax group sequential test. Sequential Analysis. 2000;19(4):193-204
Huang P, Woolson RF, O'Brien PC. A rank-based sample size method for multiple outcomes in clinical trials. Statistics in Medicine. 2008;27(16):3084-3104. PMC3163145
Huang P, Ou AH, Piantadosi S, Tan M. Formulating appropriate statistical hypotheses for treatment comparison in clinical trial design and analysis. Contemporary Clinical Trials. 2014;39(2): 294-302. PMC4254362
Huang P, Tan M. Multistage nonparametric tests for treatment comparisons in clinical trials with multiple primary endpoints. Statistics and its Interface. 2016; 9(3):343-354