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Dr. Samuel Sindayigaya

Associate Deputy Vice Chancellor of Academics (ADVCA)

Dr. Samuel Sindayigaya holds a Doctorate in Statistics with specialization in stochastic population processes, a Master’s degree in mathematical statistics from Masinde Muliro University of Science and Technology (Kenya) and his PhD in Statistics from the same university in 2017 under the scholarship of Government of Rwanda and DAAD respectively. He is a Senior Lecturer of Statistics & Probability, specifically in the area of Statistical Modelling and population stochastic processes.

He has served in different universities as lecturer of mathematics and statistics, including ULK, University of Kigali, INES-Ruhengeri, Mount Kenya University, Jomo Kenyatta University of Agriculture and Technology, University of Kigali and Potsdam University (Germany). He has extensive experience in academic administration, where he began as the Head of Department of Statistics Applied to Economy, the Dean of Faculty of Applied Fundamental Sciences (AFS) and the Deputy Vice Chancellor of Academics & Research at the Institut d’Enseignement Supérieur de Ruhengeri (INES-Ruhengeri) up to September, 2024.

Dr. Sindayigaya has also served in Higher Education Council, Rwanda for almost a decade. As a consultant, he undertook did numerous assignments in different institutions and Ministries in Rwanda, including the National Institute of Statistics of Rwanda, Rwanda Higher Education Council, Ministry of Llocal Government, the Rwanda Public Service Commission, as well as in the Ministry of Youth. He has previously collaborated with other international scholars from different recognized universities and done several presentations and seminars, mostly at German universities, notably at the Ludwig Maximillian University of Munich, Mannheim University and Potsdam University.

His research focuses on population stochastic process, demographic measures and modeling, branching process, statistical modeling and sampling techniques. In academia, Dr. Sindayigaya has developed different academic programs related to data science and statistics for both undergraduate and master’s levels. He has completed a Postdoctoral Fellowship at the Institute of Mathematics, University of Potsdam, Germany and also published a number of papers on Population Modeling and Dynamism, Population Stochastic Process with Genocide Incidence.He is the author of “A Novel Statistical Model for Poverty Estimation”. Known for his dedication, results-oriented approach, and time management skills, Dr. Sindayigaya now re-joins the University of Kigali in his new role as Associate Deputy Vice Chancellor of Academics.

Sindayigaya, S., Patrick C, Jens F., Sylivie R., (2022). Random population dynamics under catastrophic events. J.Appl.Probab.1-21 Doi:10.1017/jpr.2022.5

Samuel Sindayigaya, Nyongesa L. Kennedy , Adu A.M. Wasike (2016). The Population Mean and its Variance in the Presence of Genocide for a Simple Birth-Death -Immigration-Emigration using the Probability Generating Function. International Journal of Statistics and Analysis. ISSN 2248-9959 Volume 6, Number 1 (2016), pp. 1-8

Samuel Sindayigaya, Nyongesa L Kennedy (2015). Application of the Birth-Death Processes for Generating the Population Estimates. International Journal of Statistics and Analysis, 5, 137-149.

Sindayigaya, S. (2014). Population Growth Model as Result of Neighboring Population Growth Rate (NPGR) and Adjusted Population Growth Rate (APGR) with Application to Real Data. International Journal of Statistics and Analysis, 4, 283-292

Sindayigaya, S., Nyongesa L.K., And Wasike, A.M. (2014). Statistical Model for Poverty Estimation with Assessment of One-Cow-One Family Program in Rwanda. International Journal of Statistics and Systems, 9, 119-145.

Samuel SindayigayaAnnette W. OkothMulati Omukoba (2013). A Novel Statistical Model for Poverty Estimation. ISBN-13: ‎ 978-3-659-35612-4

Statistical Modelling, Demographic measuring and modelling, population stochastic process, analysis of Birth-death process, Probability of events, parametric and non-parametric test.

https://orcid.org/0000-0001-8651-8967

https://catalog.ihsn.org/citations/47594

https://www.amazon.ae/Novel-Statistical-Model-Poverty-Estimation/dp/3659356123

https://www.researchgate.net/publication/362722986_Random_population_dynamics_under_catastrophic_events

https://www.cambridge.org/core/journals/journal-of-applied-probability/article/abs/random-population-dynamics-under-catastrophic-events/5121309AFD018FF445041D432ED387AB