Faculty and Staff


Rebecca A Betensky

Chair of the Department of Biostatistics
Professor of Biostatistics
Dr. Rebecca Betensky's research focuses on methods for the design and analysis of studies with complex sampling, including dependent truncation and censored covariates.

Rumi Chunara

Associate Professor of Biostatistics
Associate Professor of Computer Science and Engineering, Tandon
Director of Center for Health Data Science
Dr. Chunara's research focuses on the design and development of machine learning as well as other statistical methods to address challenges related to data and goals of public health.

Stephanie Cook

Assistant Professor of Social and Behavioral Sciences
Assistant Professor of Biostatistics
Dr. Stephanie Cook’s research focus is to understand how structural- and individual-level minority stressors contribute to mental health, physical health, and health behaviors across the life span.

Alexander Dahlen

Clinical Associate Professor of Biostatistics
Dr. Alex Dahlen brings expertise in statistical science and study design to collaborate with GPH researchers and clinicians working to create innovative solutions to global public health challenges.

Yang Feng

Professor of Biostatistics
Dr. Feng's research focuses on machine learning methods with applications in public health, nonparametric and semi-parametric methods, network data analysis, and bioinformatics.

Melody Goodman

Interim Dean, School of Global Public Health
Professor of Biostatistics
Dr. Melody Goodman researches social risk factors that contribute to health inequities among underserved communities in urban areas and develops culturally competent and evidence-based solutions.

Siyu Heng

Assistant Professor of Biostatistics
Dr. Siyu Heng's areas of expertise are in methodology research and its applications in public health.

Hai Shu

Assistant Professor of Biostatistics
Dr. Hai Shu is an expert in high-dimensional data analysis, machine/deep learning and medical image analysis.

Shu Xu

Clinical Assistant Professor of Biostatistics
Dr. Shu Xu's work represents the statistical and applied aspects of quantitative methodology, including evaluating and developing statistical methods for longitudinal data analysis.

Faculty with a Secondary Appointment in Biostatistics

Linda Collins

Professor of Social and Behavioral Sciences
Dr. Linda Collins’ interests are in the development, dissemination, and application of the multiphase optimization strategy, a framework to optimize behavioral and social-structural interventions.

Joshua Epstein

Professor of Epidemiology
Dr. Joshua M. Epstein is a world-renowned pioneer of agent-based modeling, and has applied it to a staggering array of problems in the social, behavioral, and health sciences.

Erez Hatna

Clinical Associate Professor of Epidemiology
Dr. Erez Hatna researches geoinformatics, spatial analysis, agent-based modeling, and urban systems and dynamics.


Jemar Bather

Jemar Bather

Dr. Jemar Bather’s research focuses on the novel application of statistical methods to address perennial public health challenges and advance health equity.

Jonathan Odumegwu

Jonathan Odumegwu

Prior to NYU, Dr. Jonathan Odumegwu was a Research Assistant and Instructor at the University of the New Mexico. His research focuses on phylogenetics, phylogenomic studies, and design and analysis methods in biomedical and clinical studies. Other areas of interest are Biostatistics, Mathematical Modeling, and Scientific Computing.

Brian Spitzer

Brian Spitzer

Dr. Brian Spitzer completed his Ph.D. at New York University; his research focuses on methods and psychometrics to appropriately explore diverse populations' learning orientations across their lifespan.

       Adjunct Faculty

  • Cassandra Arroyo-Johnson, PhD (Assistant Professor of Surgery
    Washington University School of Medicine)
  • Yuyu (Ruby) Chen, PhD Candidate, Biostatistics, NYU School of Global Public Health
  • Jasmin Choi, PhD Candidate, Social and Behavioral Sciences, 
    NYU School of Global Public Health
  • Mithat Gönen, PhD (Chief of Biostatistics at Memorial Sloan Kettering Cancer Center)
  • Daniel Hagen, PhD Research Scientist, NYU School of Global Public Health
  • Chuck Huber, PhD (Director of Statistical Outreach at StataCorp)
  • Katherine Panageas, DrPH (Attending Biostatistician and Director of Research Support at Memorial Sloan Kettering Cancer Center)
  • Zuofeng Shang, PhD (Associate Professor of Mathematical Sciences at NJIT)
  • Antai Wang, PhD (Associate Professor, Mathematical Sciences at New Jersey Institute of Technology)
  • Jianan Zhu, PhD Candidate, Biostatistics, NYU School of Global Public Health


Vardia Duterville picture

Vardia Duterville

Program Administrator 
Cindy Martinez

Cindy Martinez

Administrative Aide
Evan Wardell picture

Evan Wardell

Administrative Aide


Faculty Labs

NYU’s School of Global Public Health houses many dynamic centers, labs, initiatives and programs, each offering mentorship, collaboration with faculty and a chance to hone your skills in innovative, action-based learning settings. These are examples of such labs led by our department's own faculty; more from around GPH can be found here. (Please also see individual faculty pages for more on their research.)

Attachment and Health Disparities Research Lab (Dr. Stephanie Cook)

The Attachment and Health Disparities Lab seeks to understand health disparities observed among young sexual and racial/ethnic minorities through the lens of Dr. Cook’s integrated theory of adult attachment and minority stress.

Though current theoretical paradigms of attachment indicate how individuals respond to stress, these theories do not adequately account for the unique impact of social stressors on individual health and well-being, which may be of critical importance in understanding the drivers of health in marginalized populations. The negative social valuation of a marginalized identity—such as a sexual minority identity or a racial minority identity—causes stress in persons with a marginalized social status beyond the level of stress that people generally experience; this excess stress has been named minority stress.

However, many theories of minority stress are limited and inadequately delineate the associations between attachment orientation, stress, and subsequent health outcomes.  Making these theoretical and empirical linkages is important for understanding how to address health disparities among disadvantaged individuals who are at heightened risk for experiencing minority stress compared to other individuals (e.g., African-American youth, sexual minority men). Therefore, one of the main objectives of Dr. Cook’s research is to understand the pathways and mechanisms located particularly at the intersection of marginalized identities that link attachment, minority stress, and health among disadvantaged individuals.

Biostatistics Consulting Lab (Dr. Rebecca Betensky)

The biostatistics consulting lab (also known as GPH-GU 3235 Biostatistical Consulting when offered as a formal course), led by Dr. Rebecca Betensky, is an initiative in which students work to provide statistical support on real-world studies being performed throughout the NYU community, with our predominant partnerships taking place with researchers at the School of Medicine and GPH. In addition to experience working with real data, these partnerships can also lead to co-authorship and summer research opportunities.

For more information on upcoming meetings (or for requesting statistical support on a study), please visit our Consulting Lab page.

The Chunara Lab (Dr. Rumi Chunara)

The overarching goal of our research is to develop computational and statistical approaches for acquiring, integrating and using data to improve population-level public health. We focus on the design and development of data mining and machine learning methods to address challenges related to data and goals of public health, as well as fairness and ethics in the design and use of data and algorithms embedded in social systems.

Visit the Chunara Lab website here

Feng Lab (Dr. Yang Feng)

Led by Dr. Yang Feng in the Department of Biostatistics at CGPH, the Feng Lab seeks to develop and apply machine learning (ML) and big data methods to solve public health problems.  In addition, Feng Lab is interested in high-dimensional data analysis and modeling, network models, nonparametric and semiparametric methods, and bioinformatics. 

Feng Lab is actively looking for motivated talents at undergraduate, master and Ph.D. levels. If you are interested, please submit an application here.

Measurement, Learning, & Evaluation Lab (Dr. Melody Goodman)

Measurement, Learning, & Evaluation (MLE) lab director Melody Goodman and the multidisciplinary team members are committed to developing, implementing, and evaluating specific solutions to address measurement gaps in research and practice to address health disparities. As a biostatistician and health disparities methodologist, Dr. Goodman challenges her team members to work collaboratively with community health stakeholders to address pressing issues affecting the health of minority and medically underserved communities. The MLE lab conducts mixed-methods (qualitative/quantitative) community-engaged research focused on rigorous measurement, engages in scientific learning using data-driven approaches, and implements comprehensive (formative, summative, impact) evaluation.

MLE has two primary research tracks: 1) an applied methods track with an emphasis on survey research and a strong focus on measurement/measure development, and (2) a community-engaged research track with a focus on enhancing the infrastructure for community-engaged research through academic-community collaborations and through the development, implementation, and evaluation of community-engaged research projects and programs to reduce health disparities. In addition, MLE conducts collaborative work to support research teams/community-academic partnerships with study design, survey instrument development, data management, statistical analysis, and program/project evaluation.

Visit the MLE Website

Xu Quantitative Lab (Dr. Shu Xu)

The Xu Quantitative Lab led by Dr. Shu Xu focuses on the application and evaluation of innovative quantitative methods to social science and public health research. Our mission is to reinvent the public health paradigm by inspiring innovative scholarship, practice and leadership across boundaries. The primary research track of this lab is (but not limited to) tobacco use and health behavior change using Population Assessment of Tobacco and Health (PATH) data; and is centered on various aspects of latent growth models, missing data methods, causal inference models, and developing statistical methods for longitudinal data analysis. We work to understand and address the health effects of tobacco use; assess the effects of tobacco use patterns on various health outcomes; tobacco cessation and control strategies; effects of tobacco on various population groups; assess and evaluate the tobacco campaigns and policies.

For more information, please contact Dr. Shu Xu at sx5@nyu.edu.