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Marie-Abèle Bind, PhD

Marie-Abèle Bind is an Assistant Professor of Medicine at Harvard Medical School and Assistant Investigator at MGH Biostatistics. Her research interests focus on defining the causal questions being asked by describing real or hypothetical multi-factorial interventions, developing causal inference methods for quantifying the effects of randomized and non-randomized exposures on health outcomes and understanding the mechanisms explaining these health effects. Her current research has been funded by the NIH Early Independence Award program.

Dr. Bind completed her joint PhD in Biostatistics and Environmental Health at the Harvard School of Public Health, working with Professors Brent Coull and Joel Schwartz. She then became a Ziff postdoctoral Fellow at the Harvard University Center for the Environment. In 2016, she was awarded an Early Independence Award (NIH High-Risk High-Reward research grant) and became Research Associate in the Department of Statistics. From 2017 to 2021, she became a John Harvard Distinguished Science Fellow. 

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David Cheng, PhD

David Cheng is an Instructor of Investigation at MGH and an Instructor in Medicine at HMS. He collaborates with multiple groups at Mass General, including the Division of General Internal Medicine and the Mongan Institute. His collaborative research includes work in cancer, autoimmune diseases, and cardiovascular diseases. His methodological research is in causal inference and data integration. He is particularly interested in developing methods and applications to facilitate comparative effectiveness research and precision medicine using electronic health records data.

Dr. Cheng received his PhD in Biostatistics from Harvard University in 2018 and also holds an AM in Biostatistics from Harvard and a BA in Economics and Statistics from the University of Chicago.

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Lori Chibnik, PhD

Lori Chibnik is a biostatistician and Assistant Professor with an appointment in the Department of Neurology at Massachusetts General Hospital and the Department of Epidemiology at the Harvard T.H. Chan School of Public Health. She received her MPH in International Health and her PhD in biostatistics from the Boston University where she worked on predictive modeling methods for disease risk.

Over her career, she has developed and assessed predictive models for diseases such as autoimmune diseases, HIV and pre-natal screening and continues to apply her methods to complex diseases. Her current research focuses primarily on genetics and genomics of Alzheimer’s Disease and dementia with an emphasis on longitudinal cohorts and cognition. She serves as the co-lead of the Data and Statistics Core of the Massachusetts Alzheimer’s Disease Research Center (MADRC) and Director of the Biostatistical Consulting Service in the Dept. of Neurology.

In addition to her research, she is internationally renowned for her training programs and innovative teaching techniques, having developed multiple courses in biostatistics for varied audiences, most recently a series specific to the needs of scientists in sub-Saharan Africa. Currently she directs the Global Initiative for Neuropsychiatric Genetics Education and Research (GINGER) program at the Harvard-Chan School and the Broad Institute of MIT and Harvard.

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Dianne Finkelstein, PhD

Dianne Finkelstein is a Professor of Medicine at Harvard Medical School, Professor in the Department of Biostatistics at the Harvard T.H. Chan School of Public Health, and a biostatistician at Massachusetts General Hospital.

After ten years of leadership, she recently stepped down as Director of MGH Biostatistics. Her research interests focus on cancer clinical research and statistical methods for survival analysis and longitudinal outcomes in clinical trials and epidemiology studies.

Dr. Finkelstein earned a Ph.D. in Biostatistics from the University of Michigan.

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Andrea S. Foulkes, ScD

Andrea S. Foulkes is Director of Biostatistics at Massachusetts General Hospital, Professor of Medicine, Harvard Medical School and Professor, Department of Biostatistics, Harvard T.H. Chan School of Public Health. Under her leadership, MGH Biostatistics faculty and staff serve as lead statisticians on over 170 NIH sponsored research projects across 28 MGH divisions and departments and contribute to $489 million in research funding.  

Dr. Foulkes has a 20-year active research program in statistical methods for precision medicine using high-dimensional molecular and cellular level data to inform clinical risk factors for complex disease phenotypes at the intersection of infectious disease and cardiovascular disease. Her statistical methods research is motivated and grounded in HIV/AIDS, cardiometabolic disease, inflammation and SARS-CoV-2/COVID-19 research. As PI on multiple NIH-funded awards, she is leading efforts to develop and evaluate principled statistical methods for interrogating the mechanistic underpinnings of complex diseases. 

Dr. Foulkes earned a ScD in Biostatistics from Harvard University and a BA in Mathematics from Brown University. 

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Musie Ghebremicheal, PhD

Musie Ghebremichael is an Associate Professor at Harvard Medical School, an Associate Investigator at MGH Biostatistics and Director of Biostatistics and Database Cores at the Ragon Institute of MGH, MIT and Harvard. His primary research interest focuses on the application and development of statistical methods for HIV/AIDS, TB, and immunologic research.   

Dr. Ghebremichael earned his Ph.D. in Statistics from Rice University and did a post-doctoral fellowship at Yale University.   

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Douglas Hayden, PhD

Douglas Hayden is an Assistant Professor of Medicine at Massachusetts General Hospital and the Harvard Medical School. He has training in pure mathematics and twenty-five years of professional practice in clinical research. His expertise includes direct collaboration with clinical investigators on development and analysis of single center studies as well as extensive experience with design, analysis, and support of national multi-center studies, primarily in critical care.

Dr. Hayden is a consulting biostatistician for Harvard Catalyst and holds a PhD in mathematics from Boston University.

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Brian Healy, PhD

Brian Healy is an Associate Professor of Neurology at Harvard Medical School (HMS) and an Associate Professor in the Department of Biostatistics at the Harvard T.H. Chan School of Public Health. He is the primary biostatistician for the Partners MS Center at Brigham and Women’s Hospital, and he is a member of Massachusetts General Hospital (MGH) Biostatistics. Dr. Healy has been the instructor for many courses related to biostatistics at HMS and Harvard T.H. Chan School of Public Health. Dr. Healy’s research focuses on modeling the disease course in patients with multiple sclerosis.

He obtained his PhD in Biostatistics from the Harvard T.H. Chan School of Public Health in 2007.

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Susanne S. Hoeppner, PhD

Susanne S. Hoeppner is an Assistant Professor of Psychiatry at Harvard Medical School (HMS) and is a member of Massachusetts General Hospital (MGH) Biostatistics. She provides statistical guidance and expertise for various groups at MGH including the Center for OCD and Related Disorders (CORD), the Medical Practice Evaluation Center (MPEC), and the Recovery Research Institute (RRI). Her collaborative research effort has included applications in psychology, psychiatry, smoking cessation, and HIV/AIDS. She has served as the principal statistician on pivotal trials approved by the FDA and has designed and analyzed Phase I-III studies in addiction, psychiatry, and psychology.  She also has ample experience setting up, updating, and overseeing the use of electronic data capture forms as implemented via REDCap, having designed and managed such databases for several single- and multi-site clinical trials at MGH.  Dr. Hoeppner’s clinical interests are in dynamic health behavior modeling and positive psychology.

Dr. Hoeppner earned a PhD in Oceanography and Coastal Sciences and her Master of Applied Statistics from Louisiana State University.  She also holds a MS in Biological Science from Southeastern Louisiana University.