Doctor Farai Mlambo

Farai holds a strong academic background with several qualifications. He is currently pursuing a PhD in Computer Science (2023 - Present) at the University of Johannesburg, focusing on Probabilistic Machine Learning - Uncertainty Quantification with Deep Learning. He also holds a PhD in Mathematical Statistics (2015 - 2019) from Nelson Mandela University, where his thesis focused on Wavelet Theory Application for Economic and Financial Time Series. He received the Best Paper Award at the European Simulation and Modelling Conference (2019) and the Innovation Doctoral Scholarship Award from the National Research Foundation.

His other qualifications include a Master of Commerce in Statistics Research (Cum Laude) (2013 - 2014), BCom Honours in Mathematical Statistics (Cum Laude) (2012), and a BCom in Economics and Statistics (Cum Laude) (2009 - 2011), all from Nelson Mandela University (NMU). Throughout his studies, Farai earned numerous awards, including Best Honours Graduate, Best Initial Degree Award, and multiple subject-specific accolades in Economics and Statistics. He was also awarded a National Presidential Scholarship by the Government of Zimbabwe.

Farai has extensive experience in teaching and research across various disciplines. Specialising in statistical, mathematical, and computational methods for interdisciplinary studies, he served as a full-time lecturer in Mathematical Statistics at the University of the Witwatersrand (Wits University) in Johannesburg, South Africa, where he taught various courses for seven years. Prior to this, he held contract positions as a statistical analyst, institutional researcher, and lecturer at Fever Tree Finance, the Office of the Vice-Chancellor, and the Department of Statistics at Nelson Mandela University.

Farai also leads the Statistical Machine Learning, Data Science, and Analytics Lab (SMLDSA Lab), a virtual platform connecting a network of postgraduate students, academics, and industry partners. The lab hosts around 20 postgraduate students—Honours, Masters, and PhD candidates—from institutions like the University of the Witwatersrand and the University of Johannesburg. Within this collaborative environment, students engage in cutting-edge research in areas such as Bayesian Neural Networks, Gaussian Processes, Geographically Weighted Regression, and Uncertainty Quantification. Under Farai's leadership, the lab bridges academia and industry, promoting partnerships that address complex real-world challenges across sectors like business, healthcare, and engineering. Industry partners collaborate with students and academics, offering practical insights while accessing advanced machine learning solutions.

Farai's teaching portfolio spans undergraduate and postgraduate courses in mathematics, statistics, data science, and economics. He notably coordinated a large course with approximately 1,200 students annually at Wits for six years, earning recognition as Best Lecturer twice. Over the past decade, Farai has taught extensively at both Wits and NMU, and his research interests include artificial intelligence, machine learning, statistics, and data science, with practical applications in business, engineering, and healthcare. He has successfully supervised approximately 20 postgraduate students to completion and has published numerous research articles in peer-reviewed journals, conference proceedings, and books, underscoring his dedication to advancing knowledge in his fields of expertise.

In addition to his teaching and research roles, Farai has served as a Board Member of the Faculty of Commerce, Law, and Management (CLM) at Wits, representing the Faculty of Science. His contributions in teaching, administration, and research have earned him several academic awards for excellence in research, teaching, and overall academic achievement.

Peer Reviewed Journal Articles Published

2022: Farai Mlambo, Cyril Chironda & Jaya George: Machine Learning for the Diagnosis and Risk Stratification of COVID-19 using Routine Laboratory Data. Feature Papers

on COVID-19, Infectious Disease Reports. Multidisciplinary Digital Publishing Institute.

2022: Herbert Hove & Farai Mlambo: On Wiener Process Degradation Model for Reliability: A Simulation Study. Modelling and Simulation in Engineering. Hindawi.

2022: Farai Mlambo & David Mhlanga: Artificial Intelligence and Machine Learning for Energy in South Africa. Africagrowth Agenda. Vol. 19 Issue 4. Africagrowth Institute.

Peer Reviewed Conference Proceedings Published

2024: Igor Litvine & Farai Mlambo: Persistence And Long Memory In Random Processes. Conference Proceedings of the 38th European Simulation and Modelling Conference.

EUROSIS. SIM-METH-07 – ESM2024. San Sebastian - October 23-25.

2019: Farai Mlambo & Igor Litvine: Wavelet Theory: for Economic and Financial Cycles. Conference Proceedings of the 33rd European Simulation and Modelling Conference. EUROSIS. FUZ07 – ESM2019, p148-158. EUROSIS-ETI. ISBN: 978-9492859-09-9, Palma de Mallorca, October 2019. Paper awarded the Best Paper Award at ESM2019.

2014: Farai Mlambo & Igor Litvine: Causality Test for Non-Stationary Time Series. Conference Proceedings of the 28th European Simulation and Modelling Conference. EUROSIS. METH11 –ESM2014, p29-31. EUROSIS-ETI. ISBN: 978-90-77381-86-1, Porto – October 2014.

Peer Reviewed Book Chapters Published

2024: David Mhlanga, Farai Mlambo & Mufaro Dzingirai: Harnessing Artificial Intelligence and Machine Learning for Enhanced Agricultural Practices: A Pathway to Strengthen Food Security and Resilience. Book Series: Fostering Long-Term Sustainable Development in Africa: Overcoming Poverty, Inequality, and Unemployment..

SPRINGER.

2023: Farai Mlambo, Cyril Chironda, Jaya George & David Mhlanga: The Role of Machine Learning and Artificial Intelligence in Improving Health Outcomes in Africa During and After the Pandemic: What Are We Learning on the Attainment of Sustainable Development Goals? Book Series: The Fourth Industrial Revolution in Africa. SPRINGER.

2023: Farai Mlambo & David Mhlanga: A Machine Learning Approach for Predicting

Emissions Based on GDP: A Case of South Africa in Comparison with the United Kingdom. Book Series: The Fourth Industrial Revolution in Africa. SPRINGER.

2023: David Mhlanga & Farai Mlambo: Post-Independence Sustainable Development in Africa and Policy Proposals to Meet the Sustainable Development Goals. Book Series:

Post-Independence Development in Africa. SPRINGER.

2023: David Mhlanga & Farai Mlambo: The Potential of the Fourth Industrial Revolution to Promote Economic Growth and Development in Africa. Book Series: The Fourth

Industrial Revolution in Africa. SPRINGER.