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Department

Statistics

EXPERTS

  • Carla Goad
    • Professor
    • Statistics
    • ProfessorStatistics
    Carla L. Goad is a Professor of Statistics at Oklahoma State University. She holds a Ph.D. in Statistics from Kansas State University. Her areas of expertise are experimental design and analysis, SAS Programming, and linear models. She is a statistical consultant for the Oklahoma Agriculture Experiment Station and has enjoyed working with agricultural researchers in animal and plant sciences. Through these collaborations she has coauthored many articles in agriculture research journals.
    Carla L. Goad is a Professor of Statistics at Oklahoma State University. She holds a Ph.D. in Statistics from Kansas State University. Her areas of expertise are experimental design and analysis, SAS Programming, and linear models. She is a statistical consultant for the Oklahoma Agriculture Experiment Station and has enjoyed working with agricultural researchers in animal and plant sciences. Through these collaborations she has coauthored many articles in agriculture research journals.
    • Faculty/Staff
    • Oklahoma State University - Stillwater
    • Statistics
    Fields of Research
    • Agricultural, veterinary and food sciences
    • Applied statistics
    • Agricultural and veterinary sciences
    • Biological sciences
    • Crop and pasture production
    • Plant biology
    • Soil sciences
    • Statistics
  • Joshua Habiger
    • Professor
    • Statistics
    • ProfessorStatistics

    I earned a BS in Mathematics and MS in Statistics from Kansas State University in 2004 and 2006, respectively.  In 2010 earned a PhD in Statistics from the University of South Carolina and joined the Department of Statistics as an assistant professor.  I was promoted to associate professor in 2016 and promoted to professor in 2021.  

     

    I enjoy developing new statistical theory and methods for the analysis of high dimensional (HD) data, especially those aimed at variable or model selection motivated by the analysis of HD count data arising in the "omics" or imaging. I find it particularly rewarding when the need for methodological development arises with collaborators, and results in new statistical methodology that is implementable broadly (ex. R package).  Recently I have become interested in replicability and meta analysis.  Here the goal is to assess and address replication and/or false discovery rates using, say, a collection of p-values or summary statistics that may be subject to selection or publication bias.  I also enjoy developing theory for p-value statistics with discrete distributions, such as mid-p-values, randomized p-values and natural p-values.  Here the goal is to develop theoretically sound p-values for downstream analysis, like multiple hypothesis testing or meta analysis. 



    Keywords: False Discovery Rate; High Dimensional Data; Applications in "omics"; Categorical Data Analysis; Statistical Machine Learning Applications; Classification Analysis; Model Selection; Replicability Analysis; Multiple Hypothesis Testing; Model Selection

     

    I earned a BS in Mathematics and MS in Statistics from Kansas State University in 2004 and 2006, respectively.  In 2010 earned a PhD in Statistics from the University of South Carolina and joined the Department of Statistics as an assistant professor.  I was promoted to associate professor in 2016 and promoted to professor in 2021.  

     

    I enjoy developing new statistical theory and methods for the analysis of high dimensional (HD) data, especially those aimed at variable or model selection motivated by the analysis of HD count data arising in the "omics" or imaging. I find it particularly rewarding when the need for methodological development arises with collaborators, and results in new statistical methodology that is implementable broadly (ex. R package).  Recently I have become interested in replicability and meta analysis.  Here the goal is to assess and address replication and/or false discovery rates using, say, a collection of p-values or summary statistics that may be subject to selection or publication bias.  I also enjoy developing theory for p-value statistics with discrete distributions, such as mid-p-values, randomized p-values and natural p-values.  Here the goal is to develop theoretically sound p-values for downstream analysis, like multiple hypothesis testing or meta analysis. 



    Keywords: False Discovery Rate; High Dimensional Data; Applications in "omics"; Categorical Data Analysis; Statistical Machine Learning Applications; Classification Analysis; Model Selection; Replicability Analysis; Multiple Hypothesis Testing; Model Selection

     

    • Faculty/Staff
    • Oklahoma State University - Stillwater
    • Collaborative projects
    • Mentoring (long-term)
    • Mentoring (short-term)
    • Career advice
    • Statistics
    Fields of Research
    • Statistics
    • Statistical data science
    • Bioinformatics and computational biology
  • Ye Liang
    • Professor
    • Statistics
    • ProfessorStatistics

    I am a Professor of Statistics at Oklahoma State University. Before joining OSU, I obtained my B.S. in Mathematics from Nanjing University (China) in 2006 and Ph.D. in Statistics from the University of Missouri in 2012.

     

    My research focus is Bayesian methods for statistical and machine learning inference, especially with uncertainty quantification. I'm also interested in high-dimensional, nonlinear regression problems, nonlinear state-space models, spatial models, and longitudinal models. Real world applications typically arise from medical records, epidemiological data, and ecological forecasting.

     

    I have completed multiple research projects funded by NIH, NSF, USDA, and OCAST. I serve as an Associate Editor for the journal Statistics and Computing. 



    Personal Website: https://sites.google.com/view/yeliang/home

    I am a Professor of Statistics at Oklahoma State University. Before joining OSU, I obtained my B.S. in Mathematics from Nanjing University (China) in 2006 and Ph.D. in Statistics from the University of Missouri in 2012.

     

    My research focus is Bayesian methods for statistical and machine learning inference, especially with uncertainty quantification. I'm also interested in high-dimensional, nonlinear regression problems, nonlinear state-space models, spatial models, and longitudinal models. Real world applications typically arise from medical records, epidemiological data, and ecological forecasting.

     

    I have completed multiple research projects funded by NIH, NSF, USDA, and OCAST. I serve as an Associate Editor for the journal Statistics and Computing. 



    Personal Website: https://sites.google.com/view/yeliang/home

    • Faculty/Staff
    • Oklahoma State University - Stillwater
    • Collaborative projects
    • Statistics
    Fields of Research
    • Statistics
    • Computational statistics
    • Machine learning
  • Head
    Mindy Mccann
    • Professor
    • Statistics
    • ProfessorStatistics
    Mindy McCann is Professor and Head of Statistics at Oklahoma State University. She holds a Ph.D. in Statistics from the University of South Carolina. Her areas of expertise are simultaneous inference and multiple comparisons. Before serving as Head Dr. McCann spent more than 20 years as the graduate coordinator for the department. She enjoys working with students and faculty to increase the impact and reputation of the department and the profession.
    Mindy McCann is Professor and Head of Statistics at Oklahoma State University. She holds a Ph.D. in Statistics from the University of South Carolina. Her areas of expertise are simultaneous inference and multiple comparisons. Before serving as Head Dr. McCann spent more than 20 years as the graduate coordinator for the department. She enjoys working with students and faculty to increase the impact and reputation of the department and the profession.
    • Faculty/Staff
    • Oklahoma State University - Stillwater
    • Statistics
  • Pratyaydipta Rudra
    • Associate Professor
    • Statistics
    • Associate ProfessorStatistics
    I am currently an Associate Professor of Statistics at Oklahoma State University. I obtained my PhD in Biostatistics from University of North Carolina at UNC Chapel Hill and worked as a post-doctoral fellow at University of Colorado Denver.

    Research Interests:

    Statistical Genomics, Multiple Hypothesis Testing, Test of Association, Statistical Learning and Kernel Methods, High-dimensional Data Analysis, Multivariate Analysis, Longitudinal Data Analysis, Clinical Biostatistics.

    My primary research interests lie broadly in developing statistical methodologies for large biological data sets such as 'omics' data sets. In particular, my interest span several areas such as test of association, expression Quantitative Trait Loci (eQTL) analysis, kernel machine methods, multiple hypothesis testing, longitudinal data analysis and multivariate methods. Although my research interests are varied, they are all motivated by real-world problems.

    In addition to my methodological research, I have also conducted extensive interdisciplinary and collaborative research. Collaboration is an essential component of my research activities. While it helps to establish a bridge between statistical theory and its applications to real life problems, it also inspires evolution of novel methodologies. I look forward to new collaboration opportunities in future.
    I am currently an Associate Professor of Statistics at Oklahoma State University. I obtained my PhD in Biostatistics from University of North Carolina at UNC Chapel Hill and worked as a post-doctoral fellow at University of Colorado Denver.

    Research Interests:

    Statistical Genomics, Multiple Hypothesis Testing, Test of Association, Statistical Learning and Kernel Methods, High-dimensional Data Analysis, Multivariate Analysis, Longitudinal Data Analysis, Clinical Biostatistics.

    My primary research interests lie broadly in developing statistical methodologies for large biological data sets such as 'omics' data sets. In particular, my interest span several areas such as test of association, expression Quantitative Trait Loci (eQTL) analysis, kernel machine methods, multiple hypothesis testing, longitudinal data analysis and multivariate methods. Although my research interests are varied, they are all motivated by real-world problems.

    In addition to my methodological research, I have also conducted extensive interdisciplinary and collaborative research. Collaboration is an essential component of my research activities. While it helps to establish a bridge between statistical theory and its applications to real life problems, it also inspires evolution of novel methodologies. I look forward to new collaboration opportunities in future.
    • Faculty/Staff
    • Oklahoma State University - Stillwater
    • Collaborative projects
    • Teaching opportunities
    • English
    • Bengali
    • Statistics
    Fields of Research
    • Health sciences
    • Biological sciences
    • Information and computing sciences
    • Medical and health sciences
    • Biostatistics
    • Applied statistics
    • Statistics
  • Zeyi Wang
    • Assistant Professor
    • Statistics
    • Assistant ProfessorStatistics

    Dr. Zeyi Wang is an Assistant Professor of Statistics at Oklahoma State University. He earned his PhD in Biostatistics from Johns Hopkins Bloomberg School of Public Health. Dr. Wang's research involves method development with targeted maximum likelihood estimation in longitudinal mediation, computerized and higher order efficient estimation, electronic health record data analysis, as well as reproducibility and clinical trials with brain functional connectivity.

    Dr. Zeyi Wang is an Assistant Professor of Statistics at Oklahoma State University. He earned his PhD in Biostatistics from Johns Hopkins Bloomberg School of Public Health. Dr. Wang's research involves method development with targeted maximum likelihood estimation in longitudinal mediation, computerized and higher order efficient estimation, electronic health record data analysis, as well as reproducibility and clinical trials with brain functional connectivity.

    • Faculty/Staff
    • Oklahoma State University - Stillwater
    • Statistics
  • Sangyoon Yi
    • Assistant Professor
    • Statistics
    • Assistant ProfessorStatistics
    High-dimensional statistics, Multiple testing, Statistical application in genomics and Data integration
    High-dimensional statistics, Multiple testing, Statistical application in genomics and Data integration
    • Faculty/Staff
    • Oklahoma State University - Stillwater
    • Statistics
  • Lan Zhu
    • Professor
    • Statistics
    • ProfessorStatistics
    Dr. Lan Zhu is a Professor of Statistics at Oklahoma State University. She earns Bachelor's degree in Medical Science from Peking University (P.R. China) and MS and PhD degrees in Biological Statistics and Computational Biology from Cornell University. Her primary research interest is in Biostatistics. In collaboration with researchers from multiple disciplines, Dr. Zhu and her research group utilize statistical theory and computational algorithm in the model development for targets of mechanism understanding, pattern reveal , effect assessment, and new findings from dataset.
    Dr. Lan Zhu is a Professor of Statistics at Oklahoma State University. She earns Bachelor's degree in Medical Science from Peking University (P.R. China) and MS and PhD degrees in Biological Statistics and Computational Biology from Cornell University. Her primary research interest is in Biostatistics. In collaboration with researchers from multiple disciplines, Dr. Zhu and her research group utilize statistical theory and computational algorithm in the model development for targets of mechanism understanding, pattern reveal , effect assessment, and new findings from dataset.
    • Faculty/Staff
    • Oklahoma State University - Stillwater
    • Statistics
    Fields of Research
    • Genetics
    • Agricultural, veterinary and food sciences
    • Agricultural and veterinary sciences
    • Biochemistry and cell biology
    • Crop and pasture production
    • Plant biology
    • Statistics

Department contact

  • 405-744-5684
  • 301 Math Sciences, Stillwater, Oklahoma, 74078, United States
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