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

Through computational and statistical methods, Dr. Rumi Chunara researches how unstructured data can have public health applications in the real world.

Stephanie Cook

Assistant Professor of Biostatistics
Assistant Professor of Social and Behavioral Sciences

Dr. Stephanie Cook aims to understand the pathways and mechanisms linking attachment, minority stress, and health among disadvantaged individuals.

Yang Feng

Associate 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

Associate Dean for Research
Associate Professor of Biostatistics

Dr. Melody Goodman researches social risk factors that contribute to health disparities among underserved communities in urban areas and develops culturally competent and evidence-based solutions.

Hai Shu

Assistant Professor, 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, 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.


Vardia Duterville picture

Vardia Duterville

Administrative Assistant to the Chair
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 The Chunara Lab’s research is to improve our knowledge of how and why infectious and noncommunicable diseases spread in populations. In order to do this, we harness data from sources outside traditional healthcare institutions and develop computational methodology for using these observational data sources. Major research methods used include: Information retrieval, spatio-temporal analyses, data mining, machine learning and epidemiological methods for new data sources.

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.