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Machine Learning and High Dimensional Data

Machine learning focuses on the creation, characterization and development of algorithms that, when applied to data, allow us to understand their structure, make predictions and construct counterfactual analyses. This area of research is fundamental to applied statistics and data science and drives many of their recent advancements. Our faculty actively research methodological and computational approaches to machine learning, especially in high-dimensional data and data-intensive computing, to create new tools for scientific discovery. We are particularly interested in applications of these tools to genetics, clinical trials, neuroimaging and other areas of biomedicine and we regularly collaborate with researchers in those fields.

Faculty of Interest

  • Associate Professor of Biostatistics; Affiliated Faculty, Yale Institute for Global Health

    Research Interests
    • Behavioral Sciences
    • Health Plan Implementation
    • HIV
    • Global Health
    • Causality
    • Clinical Trial
    • Biostatistics
    • Social Networking
    • Observational Study
  • Assistant Professor of Biostatistics (Biostatistics)

    Research Interests
    • Genetics
    • Immune System Diseases
    • Neurosciences
    • Computational Biology
    • Statistics
    • Gene Regulatory Networks
    • Epigenomics
    • Machine Learning
  • Assistant Professor Adjunct of Biostatistics

    Research Interests
    • Computing Methodologies
    • Mathematical Computing
    • Reproducibility of Results
    • Statistics
    • Biostatistics
    • Machine Learning
  • Department Chair and Professor of Biostatistics; Affiliated Faculty, Yale Institute for Global Health; Director, Biostatistics and Bioinformatics Shared Resource

    Research Interests
    • Economics
    • Neoplasms
    • Biostatistics
  • Elihu Professor of Biostatistics and Professor of Ecology and Evolutionary Biology; Co-Leader, Genomics, Genetics, & Epigenetics Research Program

    Research Interests
    • Algorithms
    • Bacteria
    • Bacterial Infections and Mycoses
    • Beer
    • Bread
    • Cell Transformation, Neoplastic
    • Coccidioidomycosis
    • Computing Methodologies
    • Biological Evolution
    • Fungi
    • Genetic Engineering
    • Microbiological Phenomena
    • Models, Genetic
    • Models, Theoretical
    • Mycoses
    • Neoplasm Metastasis
    • Neoplasms
    • Phylogeny
    • Viruses
    • Wine
    • Models, Statistical
    • Likelihood Functions
    • Logistic Models
    • Polymerase Chain Reaction
    • Sequence Analysis, DNA
    • Nonlinear Dynamics
    • Molecular Epidemiology
    • Gene Transfer Techniques
    • Crops, Agricultural
    • Evolution, Molecular
    • Nature
    • Sequence Analysis, Protein
    • Gene Expression Profiling
    • Public Health Informatics
    • Microarray Analysis
    • Genetic Speciation
    • Host-Pathogen Interactions
    • Genetic Phenomena
    • Mathematical Concepts
    • Organisms
    • Phenomena and Processes
  • Associate Professor of Biostatistics; Associate Professor, Biomedical Informatics & Data Science

    Research Interests
    • Genetics
    • Longitudinal Studies
    • Mental Health
    • Neurosciences
    • Psychiatry
    • Public Health
    • Computational Biology
    • Genomics
    • Informatics
    • Biostatistics
    • Electronic Health Records
    • Single-Cell Analysis
    • Machine Learning
    • Data Science
    • Multiomics
  • Associate Professor of Biostatistics

    Research Interests
    • Algorithms
    • Eye Diseases
    • Disorders of Environmental Origin
    • Pregnancy Complications
    • Probability
    • Statistics as Topic
    • Stochastic Processes
    • Virus Diseases
    • Statistical Distributions
    • Biostatistics
  • Susan Dwight Bliss Professor of Biostatistics, Professor in the Child Study Center and Professor of Statistics and Data Science, Professor of Obstetrics, Gynecology, and Reproductive Sciences; Affiliated Faculty, Yale Institute for Global Health

    Research Interests
    • Child Psychiatry
    • Epidemiology
    • Infertility
    • Mental Health
    • Pregnancy
    • Psychiatry
    • Computational Biology
    • Statistics
    • Genomics
    • Biostatistics
  • Ira V. Hiscock Professor of Biostatistics, Professor of Genetics and Professor of Statistics and Data Science

    Research Interests
    • Genetics
    • Public Health
    • Computational Biology
    • Statistics
    • Genomics
    • Proteomics
    • Biostatistics
    • Single-Cell Analysis
    • Microbiota
    • Wearable Electronic Devices
  • Associate Professor of Biostatistics

    Research Interests
    • Aging
    • Genetics
    • Mental Health
    • Psychiatry
    • Neurodegenerative Diseases
    • Biomedical Research
    • Biostatistics
    • Electronic Health Records
    • Neuroimaging