Personal profile
Overview
Dr. Rendani Mbuvha is a Senior Lecturer (Associate Professor) in Actuarial Science in the Department of Mathematics. Previously, he was a Google DeepMind Academic Fellow at Queen Mary University of London and an Associate Professor in Actuarial Science at the University of the Witwatersrand. He completed his PhD at the University of Johannesburg under the supervision of Professor Tshilidzi Marwala and Dr Ilyes Boulkaibet, concentrating on Shadow Hamiltonian Monte Carlo Methods within Bayesian Neural Networks. His research focuses on using machine learning approaches in risk management, with a particular focus on physical climate risk. He is also a co-founder of AfriClimate AI, a research community dedicated to using AI for climate resilience in Africa, and the author of "Hamiltonian Monte Carlo Methods in Machine Learning". Dr. Mbuvha is a fellow of the Institute and Faculty of Actuaries and the Actuarial Society of South Africa.
External positions
Visiting Associate Professor, University of Witwatersrand, Johannesburg
1 Jan 2025 → …
Research Fellow, United Nations University
2024 → …
Areas of expertise
- QA75 Electronic computers. Computer science
- machine learning
- actuarial science
- climate impacts
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
-
SDG 2 Zero Hunger -
SDG 3 Good Health and Well-being -
SDG 7 Affordable and Clean Energy -
SDG 8 Decent Work and Economic Growth -
SDG 9 Industry, Innovation, and Infrastructure -
SDG 11 Sustainable Cities and Communities -
SDG 13 Climate Action -
SDG 15 Life on Land -
SDG 17 Partnerships for the Goals
Fingerprint
- 1 Similar Profiles
Collaborations and top research areas from the last five years
-
Impact‐Based Skill Evaluation of Seasonal Precipitation Forecasts
Nikraftar, Z., Mbuvha, R., Sadegh, M. & Landman, W. A., Nov 2024, In: Earth's Future.Research output: Contribution to journal › Article › peer-review
Open Access -
Leveraging AI for Climate Resilience in Africa: Challenges, Opportunities, and the Need for Collaboration
Mbuvha, R., Yaakoubi, Y., Bagiliko, J., Potes, S. H., Nammouchi, A. & Amrouche, S., 7 May 2024, SSRN, p. 1-5, 5 p.Research output: Preprint/Working paper › Preprint
File133 Downloads (Pure) -
Machine Learning Approaches to Improve Accuracy in Extreme Seasonal Temperature Forecasts: A Multi-Model Assessment
Mbuvha, R. & Nikraftar, Z., 11 Mar 2024.Research output: Contribution to conference › Abstract › peer-review
-
A novel workflow for streamflow prediction in the presence of missing gauge observations
Mbuvha, R., Adounkpe, J. Y. P., Houngnibo, M. C. M., Mongwe, W. T., Nikraftar, Z., Marwala, T. & Newlands, N. K., 2023, In: Environmental Data Science.Research output: Contribution to journal › Article › peer-review
Open Access -
A Novel Workflow for Streamflow Prediction in the Presence of Missing Gauge Observations
Mbuvha, R., Adounkpe, P. J. Y., Houngnibo, M. C. M. & Newlands, N., 15 May 2023.Research output: Contribution to conference › Abstract › peer-review