Lecturer-Researcher | University of Labé | Guinea
Dr. Castro Gbêmêmali Hounmenou is a distinguished statistician and data science expert with a Doctorate in Statistics-Probability, specializing in statistical learning and data mining, complemented by degrees in Environmental Engineering and Psychology (social and professional life). With over 15 years of experience, he has contributed extensively to public health, nutrition, climate change, education, gender, citizenship, and sustainable development. Dr. Hounmenou has designed and managed complex data collection systems, conducted large-scale field surveys, performed advanced statistical analyses using R, Python, Matlab, Stata, SAS, SPSS, and Minitab, and applied GIS mapping and database management for diverse projects. His expertise extends to project planning, implementation, monitoring, and reporting, having served as Consultant-Expert in Data Science, Statistical Consultant, Researcher, Assistant Professor, and Project Coordinator for high-impact initiatives with organizations such as the World Bank, GIZ, PNUD, FAO, Care Afrique, PSI/USAID, Enabel, IDRC, and CDC. Recognized for his training and mentorship, he equips professionals and students with skills in statistical methods, research methodology, data analysis, and GIS applications while promoting research and publication in his field. Dr. Hounmenou has earned multiple awards, including Best Research Article in Biostatistics (World Top Scientists), Best Thesis Poster (African Centers of Excellence, World Bank), and Best Trainer (ProEduc/GOPA/GIZ-Benin). Currently, he teaches Artificial Intelligence at the University of Labé and conducts post-doctoral research in biostatistics at CERFIG, Conakry, advancing healthcare quality and national data systems. He is also an active author with 18 publications, 48 citations, and an h-index of 3, and maintains a presence on Scopus (ID: 57218616169) and ORCID (0000-0002-2306-6083), reflecting his significant contributions to the fields of statistics, data science, and public health.
Profiles: Google Scholar |Scopus | ORCID
Featured Publications
1. Houetohossou, S. C. A., Houndji, V. R., Hounmenou, C. G., Sikirou, R., & Kakaï, R. L. G. (2023). Deep learning methods for biotic and abiotic stresses detection and classification in fruits and vegetables: State of the art and perspectives. Artificial Intelligence in Agriculture, 9, 46–60. Cited by 40
2. Savi, M. K., Mangamana, E. T., Deguenon, J. M., Hounmenou, C. G., & Kakaï, R. G. (2017). Determination of lethal concentrations using an R software function integrating the Abbott correction. Journal of Agricultural Science and Technology A, 7, 25–30. Cited by 15
3. Hounmenou, C. G., Gneyou, K. E., & Kakaï, R. L. G. (2021). A formalism of the general mathematical expression of multilayer perceptron neural networks. Preprints. Cited by 11
4. Kate, S., Hounmenou, C. G., Amagnide, A., & Sinsin, B. (2015). Effets des changements climatiques sur les activités agricoles dans la commune de Banikoara (Nord Bénin). E-Journal of Science & Technology, 10(2). Cited by 9
5. Kate, S., Amagnide, A., Hounmenou, C. G., Hounkpatin, E. L. B., & Sinsin, B. (2015). Changements climatiques et gestion des ressources pastorales en zone agropastorale au Nord-Bénin: Cas de la commune de Banikoara. Afrique Science, 11(4), 201–215. Cited by 9