Dr. Edwiga Renald is a distinguished Tanzanian researcher and academic currently serving as a Lecturer and Researcher at the Nelson Mandela African Institution of Science and Technology (NM-AIST) in Arusha, Tanzania. With an exceptional academic background in Applied Mathematics and Computational Science, Dr. Renald has established herself as a leading figure in the integration of mathematical modelling and artificial intelligence within epidemiological research. She earned her Ph.D. in Mathematical and Computer Science and Engineering (Applied Mathematics and Computational Science) from NM-AIST, where her doctoral research, “Control of Lumpy Skin Disease of Cattle: A Mathematical Modelling Approach Coupled with Deep Learning,” combined deep learning frameworks with mathematical models to enhance disease control and prediction accuracy. She previously obtained both her MSc in the same field and a BSc in Mathematics and Statistics from Mwenge Catholic University, where she also began her academic career as a Tutorial Assistant before advancing to Assistant Lecturer and later joining NM-AIST. Dr. Renald’s professional experience spans teaching, supervising postgraduate research, and conducting high-impact studies addressing real-world epidemiological and computational challenges. Her research interests include mathematical modelling of infectious diseases, deep learning applications in epidemiology, Bayesian statistics, data assimilation, and computational biology. She has been actively involved in international research programs, including the WOLIMODs Research Program at Lappeenranta University of Technology in Finland and the TWAS-SISSA Lincei Fellowship at the Scuola Internazionale Superiore di Studi Avanzati (SISSA) in Italy, where she gained expertise in Bayesian parameter estimation and Kalman filtering techniques. Dr. Renald’s scholarly output includes multiple Scopus-indexed publications in high-impact journals such as Computer Methods and Programs in Biomedicine Update and Modeling Earth Systems and Environment. Her work demonstrates a deep commitment to improving computational epidemiology and promoting evidence-based policy decisions for disease control in Africa. She is also an active member of several professional organizations, including the African Society for Biomathematics and Tanzania Women in Mathematics, advocating for gender equity in STEM fields. In recognition of her excellence, Dr. Renald received the Professor Verdiana Grace Masanja Award for the best female graduand in Applied Mathematics and Computational Science at NM-AIST. Her research skills encompass MATLAB, Python, Java, LaTeX, and GUI development, reflecting strong computational and analytical proficiency. Driven by academic excellence, mentorship, and innovation, Dr. Edwiga Renald continues to advance interdisciplinary research at the intersection of mathematics, data science, and health, inspiring a new generation of researchers in Africa and beyond.

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Featured Publications

1. Renald, E., Amadi, M., Haario, H., Buza, J., Tchuenche, J. M., & Masanja, V. G. (2025). A comparative approach of analyzing data uncertainty in parameter estimation for a Lumpy Skin Disease model. Computer Methods and Programs in Biomedicine Update.

2. Renald, E., Tchuenche, J. M., Buza, J., & Masanja, V. G. (2025). Extinction and persistence of lumpy skin disease: A deep learning framework for parameter estimation and model simulation. Modeling Earth Systems and Environment.

3. Renald, E., Masanja, V. G., Tchuenche, J. M., & Buza, J. (2024). A deterministic mathematical model with non-linear least squares method for investigating the transmission dynamics of lumpy skin disease. Healthcare Analytics, 5, 100343.

4. Renald, E., Buza, J., Tchuenche, J. M., & Masanja, V. G. (2023). The role of modeling in the epidemiology and control of lumpy skin disease: A systematic review. Bulletin of the National Research Centre, 47(1), 141.

5. Renald, E. K., Kuznetsov, D., & Kreppel, K. (2020). Desirable dog-rabies control methods in an urban setting in Africa – A mathematical model. International Journal of Mathematical Sciences and Computing, 6(1), 38–45.

6. Renald, E., Kuznetsov, D., & Kreppel, K. (2019). Sensitivity analysis and numerical simulation of a SEIV basic dog-rabies mathematical model with control. International Journal of Advanced Scientific Research and Engineering, 5(4), 27–34.

7. Renald, E. (2025). A comparative analysis of data-driven modeling techniques for epidemiological systems using AI-assisted frameworks. Under Review in Applied Computational Mathematics.