Nancy Fleischer

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Dr. Fleischer’s research focuses on how the broader socioeconomic and policy environments impact health disparities and the health of vulnerable populations, in the U.S. and around the world. Through this research, her group employs various analytic techniques to examine data at multiple levels (country-level, state-level, and neighborhood-level), emphasizing the role of structural influences on individual health. Her group applies advanced epidemiologic, statistical, and econometric methods to this research, including survey methodology, longitudinal data analysis, hierarchical modeling, causal inference, systems science, and difference-in-difference analysis. Dr. Fleischer leads two NCI-funded projects focused on the impact of tobacco control policies on health equity in the U.S.

Xingyu Zhang

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Xingyu Zhang is a Research Assistant Professor at the School of Nursing’s Applied Biostatistics Laboratory. He received his Ph.D. in Biomedical Science concentrated on biostatistics from the University of Auckland in 2016. Prior to joining the ABL, he was a postdoctoral research fellow in epidemiology and biostatistics at Emory University, and also a visiting research scholar in medical informatics at Georgia Institute of Technology. Dr. Zhang’s research focuses on healthcare outcomes with an emphasis on study design and statistical analysis. The methods he applied include multi-level analysis, time series analysis, infection early warning modeling, medical imaging analysis, feature extraction, pattern classification, neural networks, support vector machine, natural language processing, deep learning, survival analysis, meta-analysis, etc.

Edward Ionides

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Time series analysis with applications to ecology, epidemiology, health economics, cell motion and neuroscience. Methodological work on inference for partially observed stochastic dynamic systems.

The IF2 algorithm (Ionides, EL, D Nguyen, Y Atchade, S Stoev and AA King., 2015, "Inference for dynamic and latent variable models via iterated, perturbed Bayes maps," PNAS 112:719-724).

The IF2 algorithm (Ionides, EL, D Nguyen, Y Atchade, S Stoev and AA King., 2015, “Inference for dynamic and latent variable models via iterated, perturbed Bayes maps,” PNAS 112:719-724).