The Biostatistics and Bioinformatics department engages in methodological and collaborative research and directs four educational degree programs: the Clinical Research Training Program (CRTP), the Master of Biostatistics Program, the PhD Program in Biostatistics, and the Master of Management in Clinical Informatics (MMCi). Whether developing computational methods algorithms or modeling molecular, clinical, epidemiological dynamics, or engineering new biomedical applications, all faculty members share a focus on transforming biomedical science and healthcare delivery. Faculty members are expected to contribute substantively to our educational programs through teaching and/or mentorship
The department directs four degree programs: the Master of Biostatistics Program, the PhD Program in Biostatistics, the Clinical Research Training Program, and the Master of Management in Clinical Informatics. Faculty members teach courses and supervise student research in the areas of biostatistics, computational biology, statistical genetics, epidemiology, health economics, health services research and computational medicine.
Faculty and staff within the department engage in methodological and collaborative research with a wide range of investigators across Duke University.
The department encompasses a diverse community of faculty and research staff who focus on both methodological and collaborative research. Departmental investigators engage in a range of quantitative topics including biostatistics, clinical trials, genetics and genomics, biomedical informatics, biomedical quantitative science and health data science research. Learn more about the research interests of our faculty and staff here.
The department includes over 50 primary faculty, 15 secondary or adjunct appointed faculty and over 25 research staff.
All applicants to the Master of Biostatistics Program must complete and submit an online ApplyYourself application.
All applicants to the PhD Program in Biostatistics must complete and submit an online ApplyYourself application through the Duke University Graduate School.
Biostatistics:Causal inference,Semiparametric or nonparametric,Survival Analysis
Clinical Research: Clinical Trial Design / Risk Based Modeling, Comparative Effectiveness, Non-Inferiority Analysis, Outcomes and Health Services Research, Predictive Medicine
Biostatistics:
Clinical Research: Clinical Trial Design / Risk Based Modeling
Biomedical Informatics: Electronic Health Records Data, Learning Health, Patient Reported Outcomes, Precision Medicine, Translational Research
Biostatistics: Categorical data analysis,Clustering,Generalized linear models,Hierarchial models,Longitudinal or dependent data,Meta-Analysis,Mixed effect models,Missing or mismeasured data, Observational Studies, Prognostic and predictive models,Risk assessment,Semiparametric or nonparametric,Sequential Analysis,Stochastic Modeling,Survival Analysis
Clinincal Resarch: Clinical Trial Design / Risk Based Modeling,Non-Inferiority Analysis,Outcomes and Health Services Research,Predictive Medicine
Bioinformatics: Omics, Variant Calling
Biostatistics: Bayesian models, Causal inference, Semiparametric or nonparametric
Statistical Genetics and Genomics: Admixture Mapping, Disease Gene Discovery, Gene Mapping, Gene Regulation, Genetic Epidemiology, Genetic Variation, Haplotype Analyses, Population Genetics, Population Structure, Statistical Genetics, Transcriptomics
Biostatistics: Bayesian Models
Biomedical Informatics: Convolutional Neural Networks, Machine Learning
Bioinformatics: Data Integration
Biomedical Informatics: Electronic Health Records Data,Integrative Data Analysis,Patient Reported Outcome,Precision Medicine,Translational Research
Biostatistics: Categorical data analysis,Clustering,Generalized linear models,Hierarchial models,Longitudinal or dependent data,Mixed effect models,Resampling methods,Risk assessment,Stochastic Modeling,Survival Analysis, Mathematical Modeling, Joint and Mathematical Modeling
Clinical Research: Clinical Trial Design / Risk Based Modeling,Comparative Effectiveness,Predictive Medicine, Cluster Randomized Trial Design and Analysis
Statistical Genetics and Genomics: Population Genetics
Biostatistics: Bayesian Models, Hierarchical Models, Stochastic Modeling, Computational Immunology, Dynamical Systems Modeling, Single Cell Analysis
Bioinformatics: Convolutional Neural Network,Data Integration,Machine Learning,Natural Language Processing,Normalization,Omics
Biomedical Informatics: Electronic Health Records Data, Integrative Data Analysis, Mobile Technology, Multi-Modal Biomedical Data, Precision Medicine, Principal and Independent Component Analysis
Biostatistics: Longitudinal or dependent data, Mixed effect models, Resampling methods, Semiparametric or nonparametric
Clinical Research: Predictive Medicine
Statistical Genetics and Genomics: Predictive Modeling, Statistical Genetics, Transcriptomics
Bioinformatics: Data Integration, Machine Learning
Biomedical Informatics: Accessible Date Structures, Electronic Health Records Data,Implementation Science,Learning Health,Precision Medicine, Visualization
Biostatistics: Prognostic and predictive models, Risk assessment
Clinical Research:Comparative Effectiveness, Outcomes and Health Services Research, Predictive Medicine
Bioinformatics: Data Integration, Machine Learning, Sequence Analysis
Biostatistics: Bayesian models, Categorical Data Analysis, Clustering, Generalized linear models
Statistical Genetics and Genomics: Gene Regulation, Genetic Technologies Dev, Genetic Variation, Predictive Modeling
Biostatistics: Longitudinal or Dependent Data, Mixed Effect Models
Clinical Research: Clinical Trial Design / Risk Based Modeling, Comparative Effectiveness, Outcomes and Health Services Research
Bioinformatics: Sequence Analysis
Biostatistics: Bayesian models
Statistical Genetics and Genomics: Admixture Mapping, Haplotype Analyses, Statistical Genetics
Bioinformatics: Convolutional Neural Network,Machine Learning,Natural Language Processing,Omics
Biomedical Informatics: Electronic Health Records Data, Image Processing,Integrative Data Analysis, Multi-Modal Biomedical Data, Principal and Independent Component Analysis
Biostatistics: Medical imaging, Prognostic and predictive models, Semiparametric or nonparametric, Survival Analysis
Clinical Research: Predictive Medicine
Statistical Genetics and Genomics: Predictive Modeling,Transcriptomics
Biostatistics: Bayesian models, Categorical data analysis, Clustering, Generalized linear models, Hierarchial models, Longitudinal or dependent data, Mixed effect models, Missing or mismeasured data, Semiparametric or nonparametric
Clinical Research: Comparative Effectiveness, Outcomes and Health Services Research
Bioinformatics: Data Integration
Biomedical Informatics: Integrative Data Analysis,Patient Reported Outcome,Precision Medicine
Biostatistics: Bayesian models,Causal inference,Hierarchial models,Meta-Analysis,Mixed effect models,Missing or mismeasured data
Clinical Research: Clinical Trial Design / Risk Based Modeling,Comparative Effectiveness
Bioinformatics: Machine Learning
https://scholars.duke.edu/person/erich.huang
Bioinformatics: Machine Learning
Biomedical Informatics: Electronic Health Records Data, Image Processing, Implementation Science, Integrative Data Analysis, Learning Health, Mobile Technology, Patient Reported Outcome, Precision Medicine, Translational Research
Biostatistics: Prognostic and predictive models, API Development, Cloud Computing, Distributed Computing
Clinical Research: Predictive Medicine
Bioinformatics: Machine Learning
Biomedical Informatics: Electronic Health Records Data, Integrative Data Analysis, SES, Environmental data, Built Environment
Biostatistics: Bayesian models, Clustering
Clinical Research: Comparative Effectiveness, Outcomes and Health Services Research
Statistical Genetics and Genomics: Genetic Epidemiology
Bioinformatics: Machine Learning
Biostatistics: Longitudinal or dependent data, Prognostic and predictive models, Semiparametric or nonparametric, Survival Analysis, Big Data Analysis
Clinical Research: Clinical Trial Design/ Risk-Based Modeling, Non-Inferiority Analysis
Biostatistics: Clustering, Longitudinal or dependent data, Missing or mismeasured data, Diagnostic tests
Clinical Research:Clinical Trial Design / Risk Based Modeling,Comparative Effectiveness,Non-Inferiority Analysis,Outcomes and Health Services Research
Biostatistics: Survival Analysis
Statistical Genetics and Genomics: Disease Gene Discovery, Gene Mapping, Genetic Epidemiology, Genetic Variation, Haplotype Analyses, Pharmacogenomics, Population Genetics, Predictive Modeling, Statistical Genetics
Bioinformatics: Machine Learning
Biostatistics: Missing or mismeasured data, Resampling methods, Semiparametric or nonparametric, Survival Analysis
Clinical Research:Clinical Trial Design / Risk Based Modeling, Non-Inferiority Analysis
Bioinformatics: Convolutional Neural Network, Machine Learning, Omics
Biomedical Informatics: Electronic Health Records Data, Integrative Data Analysis, Mobile Technology, Multi-Modal Biomedical Data, Patient Reported Outcome, Precision Medicine
Biostatistics: Bayesian models, Causal inference, Hierarchial models, Longitudinal or dependent data, Medical imaging, Mixed effect models, Semiparametric or nonparametric, Survival Analysis
Clinical Resarch: Clinical Trial Design / Risk Based Modeling, Outcomes and Health Services Research, Predictive Medicine
Statistical Genetics and Genomics: Genetic Epidemiology,Predictive Modeling,Statistical Genetics
Bioinformatics: Alignment, Data Integration, Machine Learning, Natural Language Processing, Omics, Text Mining, Sequence Analysis
Biostatistics: Bayesian models, Hierarchial models, Missing or mismeasured data, Stochastic Modeling
Statistical Genetics and Genomics: Admixture Mapping, Disease Gene Discovery, Gene Mapping, Gene Regulation, Genomic Technologies Dev, Genetic Variation, Haplotype Analyses, Population Genetics, Population Structure, Predictive Modeling, Statistical Genetics, Transcriptomics
Biostatistics: Categorical data analysis, Causal inference,Clustering, Generalized linear models, Hierarchial models, Mixed effect models, Missing or mismeasured data, Prognostic and predictive models, Resampling methods, Semiparametric or nonparametric, Survival Analysis
Clinical Research: Comparative Effectiveness, Outcomes and Health Services Research, Predictive Medicine
Biostatistics: Longitudinal or dependent data, Prognostic and predictive models, Risk assessment, Survival Analysis
Clinical Research: Outcomes and Health Services Research, Predictive Medicine
Biostatistics: Bayesian models, Categorical Data Analysis, Causal Inference, Clustering,Hierarchial Models, Longitudinal or Dependent Data
Clinical Research: Clinical Trials Design / Risk Based Modeling, Comparative Effectiveness, Outcomes and Health Services Research, Predictive Medicine, Health Care Provider Performance Evaluation
Biomedical Informatics: Precision Medicine
Biomedical Informatics: Precision Medicine, Principal, and Independent Component Analysis
Biostatistics: Mixed effect models, Semiparametric or nonparametric
Statistical Genetics and Genomics: Gene Mapping, Genetic Epidemiology, Genetic Variation, Population Genetics, Population Structure, Statistical Genetics
Clinical Research: Outcomes and Health Serivces Research
Bioinformatics: Alignment, Complex Genomic Data Management, Data Integration, Machine Learning, Normalization, Omics, Sequence Analysis, Structural Variation, Variant Calling
Biostatistics: Resampling methods, Semiparametric or nonparametric, Survival Analysis
Clinical Research: Pharmacokinetics/Pharmacodynamics
Statistical Genetics and Genomics: Admixture Mapping, Disease Gene Discovery, Genetic Epidemiology, Genomic Technologies Dev, Genetic Variation, Haplotype Analyses, Pharmacogenomics, Population Genetics, Statistical Genetics, Transcriptomics
Bioinformatics: Machine Learning
Biomedical Informatics: Image Processing
Biostatistics: Bayesian models, Generalized linear models, Hierarchial models, Semiparametric or nonparametric
Bioinformatics: Alignment, Data Integration, Omics, Sequence Analysis
Statistical Genetics and Genomics: Disease Gene Discovery, Gene Regulation, Genetic Variation, Genomic Technologies Dev, Haplogtype Analyses, Population Genetics, Statistical Genetics, Transcriptomics
Bioinformatics: Data Integration, Standards Development Ontologies and Annotations
Biomedical Informatics: Electronic Health Records Data, Open Science
Biostatistics: Experimental Design
Clinical Research: Clinical Trial Design / Risk Based Modeling, Bioequivalence/Biosimilarity, Non-Inferiority Analysis
Biostatistics: Conflict of Interest, Education
Clinical Research: Outcomes and Health Services Research
Bioinformatics: Data Integration, Omics, Microbiome
Biostatistics: High Dimensional Statistics
Statistical Genetics and Genomics: Statistical Genetics
Clinical Research: Observational Studies
Bioinformatics:Data Integration, Machine Learning, Standards Development Ontologies and Annotations, Text Mining
Biomedical Informatics:Electronic Health Records Data, Integrative Data Analysis, Learning health,Precision Medicine, Translational Research
Clinical Research:Predictive Medicine
Biostatistics: Bayesian models, Categorical data analysis, Longitudinal or dependent data, Semiparametric or nonparametric, Sequential Analysis
Clinical Research: Clinical Trial Design / Risk Based Modeling, Outcomes and Health Services Research
Biostatistics: Categorical data analysis, Clustering, Longitudinal or dependent data, Semiparametric or nonparametric
Clinical Research: Clinical Trial Design / Risk Based Modeling,Comparative Effectiveness,Outcomes and Health Services Research
Bioinformatics: Machine Learning, Biostatistics: Hierarchial models, Semiparametric or nonparametric, Statistical Genetics and Genomics: Disease Gene Discovery, Gene Regulation, Gene Variation, Statistical Genetics, Transcriptomics
Bioinformatics: Machine Learning
Biomedical Informatics: Image Processing,Principal and Independent Component Analysis
Biostatistics: Clustering,Generalized linear models,Longitudinal or dependent data,Medical imaging,Missing or mismeasured data,Tensor Methods
Statistical Genetics and Genomics: Statistical Genetics Machine Learning
