Roland Matsouaka

Roland Albert Matsouaka

Research Fellow

Department of Epidemiology

677 Huntington Avenue
Kresge Building, Room 820
Boston, MA 02115


Dr. Roland Matsouaka is a research fellow in the Program on Causal Inference from the Department of Epidemiology at Harvard School of Public Health and a visiting scholar in the Bouvé College of Health Sciences at Northeastern University, working under the supervision of both Dr. Eric Joel Tchetgen Tchetgen and Dr. Theresa Osypuk (now at the University of Minnesota).

He received is Masters and PhD degrees from the Department of Biostatistics at the Harvard School of Public Health, working with Professors Rebecca Betensky and Tianxi Cai. He joined the Department of Epidemiology in January 2012.

Prior to coming at Harvard, Dr. Matsouaka received a Bachelor degree in Mathematics (Université Marien Ngouabi, Rep. of Congo) and two Masters degrees in Mathematics, one in Algebra (Université de Ouagadougou, Burkina-Faso) and one in Differential Geometry (Université Nationale du Bénin, Rep. of Benin). 

Although a US citizen, Dr. Roland Matsouaka was born and raised in the Republic of Congo (Central Africa). He is fluent in French, Lingala and Kikongo (both Congolese national languages) as well as in five other local languages.

Research Interests

Dr. Roland Matsouaka is a biostatistician. His primary areas of interest are in non-parametric and semi-parametric theory with application to causal inference, missing data problems, and personalized medicine

His current research is focused on how to develop statistical methods and draw inferences about treatment effects when confounding is present or suspected (e.g. in presence of selection or survivors bias). In practice, he is interested in developing reliable, efficient, and parsimonious approaches to tackle this issue. The ultimate goals being to infer causality and report results accurately in randomized clinical trials with patients’ non-compliance, informative missing or censored data and in observational studies with non-random treatment assignment.