Message from the Chair

These are exciting times for Biostatistics as public health and biomedical research and drug development collect with ever-increasing amounts of data that are of both traditional and completely novel types.  And while the world is suffering from the global pandemic of COVID-19, we have an increasingly critical role to play as interpreters of data.  Biostatistics at NYU GPH is strong and expanding new course offerings, an advanced certificate in Public Health Data Science (under review), new areas of research focus and increasing numbers of students.  We currently have approximately 100 MS and MPH students and are very excited to welcome our first cohort of 2 PhD students! 

Our faculty work on a broad array of methodological and collaborative research, including

  • foundational issues of inference such as significance testing, inference for network models, Neyman Pearson classification
  • high-dimensional statistics, deep learning, nonparametric statistics, network modeling for public health and biomedical data that feature noise accumulation, spurious correlations and complex dependencies
  • methods for censored and truncated survival data
  • efficient clinical trial design, including adaptive n-of-1 trials for Alzheimer’s disease
  • mixed-methods  (qualitative/quantitative) community-engaged research focused on rigorous  measurement
  • survey research for community- based interventions and health disparities research
  • methods for resolving high- granularity measures of disease incidence and risk from person-generated data  (social media, mobile tools, wearables, etc.)
  • spatio-temporal and machine learning methods for incorporating unstructured data in population disease modeling
  • zero-inflated count models for understanding substance use, smoking behaviors, sexual risk-taking over time
  • time diary methodology to understand the temporal associations between daily behaviors,  perceptions, of individual health.
  • latent (unmeasured) variables methods
  • collaborative research in Alzheimer’s disease, computer vision, bioinformatics, health disparities, minority stress, tobacco use, family violence, neuro-imaging


Our students have embraced the opportunities afforded to them by our popular Journal Club, professional development events, and biostatistics consulting lab.  I am greatly impressed by the thesis projects that the second year students complete, which display their engagement in collaborative Public Health research, their strong competence and creativity in the application of statistical methods, and their highly professional written, visual and oral communication skills.  When they complete their degrees, our students are well-prepared for a wide range of careers in public health, biomedical sciences, and any pursuit that involves quantitative research and/or data analysis.

In short, we are excited and energized as we develop into a great department of Biostatistics that features unique areas of expertise in areas that are highly relevant to Public Health and are applicable more broadly to all settings of inquiry that is based upon data.

Please learn more about us in these pages of our website!


Rebecca Betensky
Chair of the Department of Biostatistics
Professor of Biostatistics
+1 (212) 992-3722