Aweke Mitku

Trainee Type:

Post-doctoral

Research Topic:

Spatio-Temporal Modelling of the Effects of Climate Change and the Impact of Particulate Matter Air Pollution on Under-Five Mortality in Sub-Sahara Africa

Associated Institution:

University of the Witwatersrand, South Africa

Supervisor(s):

Dr Yolandi Ernst, Prof Tobias Chirwa and Prof Kandala.

ORCID ID: 0000-0002-1893-5344

Dr Aweke Mitku is a Postdoctoral Fellow in Biostatistics at the Global Change Institute, University of the Witwatersrand in Johannesburg, South Africa. He completed his PhD in Biostatistics from the University of KwaZulu-Natal in 2020 and worked as an assistant professor at Department of Statistics, College of Science, Bahir Dar University, Ethiopia. His postdoctoral research focuses on spatio-temporal statistical methods to study the relationship between climate change and PM2.5 air pollution on under-five mortality in Sub-Saharan Africa. His work represents an important intersection of advanced statistical methodology, climate change, and public health research in the African context.

Awol Seid Ebrie

Trainee Type:

Post-doctoral

Research Topic:

Applications of Artificial Intelligence (AI) and Machine Learning (ML) Algorithms for Disease Prevention and Personalized

Associated Institution:

University of the Witwatersrand, South Africa

Supervisor(s):

Prof Eustasius Musenge and Prof Tobias Chirwa

ORCID ID: 0000-0002-9374-7538

Awol Seid Ebrie is a post-doctoral fellow in Biostatistics at the Wits School of Public Health (SPH), University of the Witwatersrand, Johannesburg, South Africa. He holds a Ph.D. in Industrial Data Science & Engineering from Pukyong National University and Pusan National University, South Korea (2021–2024); an M.Sc. in Biostatistics from Jimma University (2010–2012) and a B.Sc. in Statistics from the University of Gondar (2005–2008), Ethiopia. With extensive academic experience in Ethiopian higher education institutions, Awol has a strong background in biostatistical methodologies, machine & deep learning algorithms, and data science applications.

His post-doctoral research focuses on developing AI and machine learning algorithms for disease prevention and personalized treatment, employing cutting-edge methodologies such as deep neural network-based causal inference, explainable AI (XAI), convolutional neural networks (CNN), and other state-of-the-art techniques. Beyond research, he is dedicated to enriching the academic environment at Wits SPH by participating in the teaching-learning process, mentoring students, conducting short-term trainings, and organizing workshops and seminars on emerging advancements in biostatistical and data science methodologies.

Awol is also committed to fostering collaborations and engaging in interdisciplinary public health studies. For collaboration opportunities or any queries, you can contact him at awol.ebrie@wits.ac.za or via WhatsApp at +27 82 401 9256

Ildephonse Nizeyimana

Trainee Type:

Post-doctoral

Research Topic:

ADVANCED DATA ANALYTICS FOR TREATMENTS EFFICIENCY IN ELDERLY PEOPLE LIVING WITH HIV IN KENYA

Associated Institution:

Moi University, Kenya

Supervisor(s):

Prof Ann Mwangi

ORCID ID: 0000-0002-1893-5344

Ildephonse Nizeyimana is a Postdoctoral Fellow in Biostatistics at Moi University. He earned his PhD in Mathematics, specializing in Statistics, in June 2024 from the Pan African University, Institute for Basic Sciences, Technology, and Innovation (PAUSTI). He has a background in Applied Mathematics from the University of Rwanda, where he served as an Assistant Lecturer in Applied Mathematics and Statistics at the College of Business and Economics since 2018. His current research focuses on Personalized Medicine, specifically examining its potential application in the treatment of elderly individuals living with HIV in Kenya.

Kevin Wamae

Trainee Type:

Post-doctoral

Research Topic:

Advancing the application of wastewater-based epidemiology (WBE) to track community health by detecting bacteria, viruses, and antimicrobial resistance in sewage

Associated Institution:

KEMRI-Wellcome Trust, Kilifi, Kenya

Supervisor(s):

Dr. George Githinji

ORCID ID: 0000-0001-7721-5534

As a Postdoctoral Researcher at KEMRI-Wellcome Trust in Kilifi, Kenya, Dr. Wamae is excited to explore the intersection of genomics, epidemiology, and public health. By analysing DNA sequences, they can uncover the hidden stories told by infectious diseases.

Training Tomorrow’s Disease Detectives: Science is a team effort, and the future depends on who we train today. He mentors students in bioinformatics and biostatistics to develop not just technical knowledge but also the networks and confidence required to succeed. This includes practical training sessions and connecting students with mentorship opportunities. He aims to raise a new generation of African scientists prepared to lead, create, and influence public health in the future.

Tracking Malaria at the Molecular Level: For his PhD and early post-doctoral work, his research work is in malaria genomics focused on solving real-world challenges. He has helped to develop laboratory workflows and bioinformatics pipelines to track how malaria parasites escape medications and diagnostics. These developments inform policy, guide treatment decisions, and increase surveillance, therefore supporting national malaria control initiatives in various African nations. By combining molecular biology with practical implementation, his work helps translate scientific innovation into frontline impact.

Wastewater Surveillance: A New Lens on Community Health: His recent post-doctoral work focuses on advancing the application of wastewater-based epidemiology (WBE) to track community health by detecting bacteria, viruses, and antimicrobial resistance in sewage—often before clinical cases emerge. WBE is scalable, affordable, and non-invasive. It offers a real-time view of pathogen circulation by capturing signals from both sick and asymptomatic people. WBE is becoming a crucial addition to clinical monitoring as global health hazards grow since it could help direct outbreak response and health policy.

LinkedIn: https://www.linkedin.com/in/kevin-wamae-ph-d-48a425263/

GitHub: https://github.com/kevin-wamae

Souand Peace Gloria TAHI

Trainee Type:

Post-doctoral

Research Topic:

Unraveling the complex interplay of environmental dynamics, socioeconomics factors and demographics determinants in tropical disease patterns in Sub-Saharan Africa: A structure equation modeling approach

Associated Institution:

University of Abomey-Calavi, Benin

Supervisor(s):

Prof. Romain Glèlè Kakaï

ORCID ID: 0000-0003-1101-2624

Souand Peace Gloria TAHI is a biostatistician, data analyst, and AI researcher. A recipient of DAAD, AI4D, and Mawazo scholarships, she conducted her PhD at the Laboratory of Biomathematics and Forest Estimation (LABEF), where she developed machine learning models to optimize maize yield prediction in Benin, integrating climate, soil, and remote sensing data.

Currently a postdoctoral researcher at LABEF, she uses structural equation modeling to explore the complex interactions between environmental, socioeconomic, and demographic factors influencing tropical disease patterns in Sub-Saharan Africa. Through her multidisciplinary research, she aims to bridge AI, agriculture, and public health for sustainable development in Africa.