Dr. Moussa Doumbia is an educator and researcher with a Ph.D. in Mathematics from Howard University (2017) and a B.A. in Mathematics from the University of the District of Columbia (2007). He has advanced data science and mathematics education, designing and teaching an introductory Data Science course, helping launch Howard University’s mathematics major with a data science concentration, and leading the proposal and development of all new courses in the new BS in Data Science program at Howard.

He is a core faculty member of the Virtual Applied Data Science Training Institute (VADSTI), co-developed Howard’s Coursera course Linear Algebra for Data Science Using Python, and participated in Microsoft’s Visiting Data Science Professor Program (2021). Dr. Doumbia has also collaborated on national research initiatives, including the Social Network Research Program with Howard University, the University of Delaware, and the NSA.

From 2024–2025, he served as a Visiting Professor at the United States Military Academy at West Point. His research spans differential privacy, infectious-disease modeling with ODEs, optimal control theory, and quantum computation. He has published on malaria incidence and supervised projects on COVID-19 data analysis and predictive modeling.

His honors include Outstanding Faculty of the Mathematics Department (2021–2022) and Best Oral Presenter at Howard University Research Day (2013). His interests include machine learning, NLP, precision health, and the theoretical modeling of infectious diseases such as malaria, TB, H1N1, and Ebola.