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Capuano, Ana
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Ana W. Capuano, MPS, MS, PhD, is an Associate Professor of Neurological Sciences in Biostatistics. She leads the Data Management and Statistical Core of the Rush Alzheimer's Disease Research Center and is a faculty biostatistician of the Rush Alzheimer’s Disease Center. She joined Rush in 2012 after concluding her PhD at the University of Iowa. She is a visiting scholar at the State Government Employee Medical Assistance Institute (IAMSP) in Brazil and Harvard T.H. Chan School of Public Health.
With hundreds of original peer-reviewed publications cited by over six thousand other scientific works, Dr. Capuano has been invited to lecture nationally and internationally, such as recent courses at South New Wales University in Australia, and Karolinska Institute in Sweden. She collaborated, consulted, and provided mentorship to several scientists on the application of modern statistical methods in epidemiological studies including the research on the association of molecular (e.g. proteomics), environmental factors (e.g. pollutants), psychiatric/psychosocial factors (e.g. stress, personality, neuropsychiatric symptoms), and comorbidities (e.g. diabetes, kidney) with age-related conditions. Capuano’s methodological interests include longitudinal models, non-linear mixed models, constrained ordinal class of models, and study design in comorbidities and disparity research. Some of the methodological developments are available in the R package nlive.
She holds elected leadership positions in multiple professional groups including elected Educational Officer of the American Statistical Association (ASA) Statistics and Data Science in Aging (SDSA) American Statistical Association, and elected incoming chair of the National Alzheimer's Coordination Center (NACC) and immediate past elected chair for the Design and Data Analytics (DaDA) Professional Interest Areas, an assembly of The Alzheimer's Association International Society to Advance Alzheimer's Research and Treatment (ISTAART). In this role, she has fostered a collaborative platform for statisticians, data scientists, and aging researchers to share their insights and experiences, discuss best practices, and exchange innovative methods and scientific findings.
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