Name: Joyce Nabende Nakatumba
Gender: Female
Title: Senior Lecturer
Department: Computer Science
Highest Qualification: PhD in Computer Science
Profile Summary
Dr. Joyce Nakatumba-Nabende holds a PhD in Computer Science from Eindhoven University of Technology, The Netherlands, a Master of Science in Computer Science from Makerere University, Uganda and a Bachelor of Computer Science from Mbarara University of Science and Technology, Mbarara, Uganda. She is a senior lecturer in the Department of Computer Science, School of Computing and Informatics Technology, College of Computing and Information Sciences. She is the current head of the Makerere Artificial Lab under the department of Computer Science. Her major research interests are in the areas of Artificial Intelligence, Machine Learning, Natural Language processing and Business Process Management. She contributes to building the capacity of African data scientists and ensures diversity and gender equity in her research.
Currently, she is a member of the Educational Advisory Committee of the Association for Computing Machinery, a board Member Data Science Africa, a member of the Responsible Artificial Intelligence (RAIN) Africa Network, a founding Member of the Open for Good Alliance Inclusive AI Commons with Localized Data by FAIR Forward and GIZ and a research scientist as part of the ARUA – The Guild Cluster of Research Excellence Addressing Global and African Challenges through Methods from Artificial Intelligence, Data Science and Theoretical and Computational Thinking.
Research Publications
1. Nakatumba-Nabende, J., Babirye, C., Nabende, P., Tusubira, J.F., Mukiibi, J., Wairagala, E.P., Mutebi, C., Bateesa, T.S., Nahabwe, A., Tusiime, H. and Katumba, A. (2024), Building Text and Speech Benchmark Datasets and Models for Low-Resourced East African Languages: Experiences and Lessons. Applied AI Letters e92. http://doi.org/10.1002/ail2.92
2. Rahman, S., Nabiryo, A.L., Tusubira, J.F., Murindanyi, S., Katumba, A. and Nakatumba-Nabende, J., 2024. Coffee and Cashew Nut Dataset: A Dataset for Detection, Classification, and Yield Estimation for Machine Learning Applications. Data in Brief, 52 p.109952. https://doi.org/10.1016/j.dib.2023.109952
3. Engineer Bainomugisha, Karen Bradshaw, Martin Mabeifam Ujakpa, Joyce Nakatumba-Nabende, Lawrence Nderu, Neema Mduma, Patrick Kihoza, and Annette Irungu. 2024. Computer Science Education in Selected Countries from Sub-Saharan Africa. ACM Inroads 15, 1 (March 2024), 64–82. https://doi.org/10.1145/3643037
4. Safari, Y., Nakatumba-Nabende, J., Nakasi, R., Nakibuule, R. A Review on Automated Detection and Assessment of Fruit Damage Using Machine Learning (2024) 10.1109/ACCESS.2024.3362230 IEEE Access https://ieeexplore.ieee.org/document/10419325 Print ISSN: 2169-3536, Online ISSN: 2169-3536, Digital Object Identifier: 10.1109/ACCESS.2024.3362230
5. Kabukye, J.K., Namugga, J., Mpamani, C.J., Katumba, A., Nakatumba-Nabende, J., Nabuuma, H., Musoke, S.S., Nankya, E., Soomre, E., Nakisige, C. and Orem, J. (2023). Implementing Smartphone-Based Telemedicine for Cervical Cancer Screening in Uganda: Qualitative Study of Stakeholders’ Perceptions. Journal of Medical Internet Research, 25, p.e45132. https://doi.org/10.2196/45132
6. Nakatumba-Nabende, J., Babirye, C., Tusubira, J.F., Mutegeki, H., Nabiryo, A.L., Murindanyi, S., Katumba, A., Nantongo, J., Sserunkuma, E., Nakitto, M. and Ssali, R. (2023). Using machine learning for image-based analysis of sweetpotato root sensory attributes. Smart Agricultural Technology, 5, p.100291. https://doi.org/10.1016/j.atech.2023.100291
Awards / Grants Won
1. Benchmarking Automatic Speech Recognition models for African Languages. Funded by Bill and Melinda Gates Foundation (2024-2025)
2. Tuberculosis in households with infectious cases in Kampala city: Harnessing health data science for new insights on TB transmission and treatment response (DS- IAFRICA-TB). Funded by Fogarty International Center (U01TW012534) (2023 -2026)
3. Amplify: Global Approaches to Responsible AI for Large Language Models (LLMs). Funded by Google (2023 – 2024)
4. Analysing ChatGPT for Cross-Lingual Localised and Targeted Agricultural Advisory for Smallholder Farmers in sub-Saharan Africa.
Funded by Bill and Melinda Gates Foundation (2023-2024)
5. Sweetpotato Genetic Advance and Innovative Seed Systems/RTB breeding: a consolidated investment. Funded by The International Potato Center (2021 -2024)
6. The Next Generation Cassava Breeding Phase 2./RTB breeding: a consolidated investment. Funded by Bill and Melinda Gates Foundation (2018 -2024)
7. Understanding Gender Biases in Building Automatic Speech Recognition Systems in the African Context. Funded by Initiative Prospective Agricole et Rurale (2023-2024)
Teaching Interests
- Machine Learning
- Data Mining
- Data Analytics and Visualisation
- Emerging Trends in Computer Science
- Modelling and Simulation
Research Interests
- Artificial Intelligence
- Machine Learning
- Natural Language Processing
- Responsible AI
Professional Body Memberships:
Association for Computing Machinery
Students Supervised
PhD
1. Ronald Opio (2024) Examining the Impact of Short–lived Climate Forcers on temperature and precipitation over Eastern Africa
2. Jennifer Aduwo (2020) A Machine Learning Model for Automatic Field Detection and Classification of Cassava Mosaic Disease
3. Rose Nakibuule (2020) Traffic Flow Speed and Congestion Monitoring in Resource Constrained Crowded Cities
MSc Students
1. Conrad Suuna (2024) Gender Bias Mitigation and Evaluation in Luganda to English Machine Translation Models
2. Raymond Nambale (2024) Using Convolutional Neural Networks for Data-driven Weather Forecasting
3. Simon Alex Twine (2024) A Multi-level Image Denoising Architecture and Toolkit using Autoencoders
4. Byron Sserubiri (2024) Detecting Coccidiosis in Poultry Using Deep Convolutional Neural Networks
5. Brenda Burundi Bashemera (2023) A Deep Learning Approach for Breast Cancer Diagnosis in Ultrasound Images
6. Jonathan Mukiibi (2023) Topic Classification for Radio Monitoring Using Deep Neural Networks
7. Daniel Namanya (2023) Improving the Key Generation Process of RSA Algorithm
8. Kenneth Awio Ogwal (2022) A Detection Model for User-to-Root Attacks using the Adaboost Classifier
9. Ezra Alisha Rwakazooba (2022) Automated Intestinal Parasite Detection in Stool Samples Using Custom Convolutional Neural Networks
10. David Kabiito (2021) Targeted Aspect-based Sentiment Analysis for Ugandan Social Media Reviews
11. Lillian Muyama (2021) Automated Detection of Tuberculosis using Transfer Learning Techniques
12. Daniel Ogenrwot (2021) Using Machine Learning to Understand the Association of Design Smells with Role-Stereotypes in Software Systems
13. Thon Kuir Biar Ayual (2021) Quantitative Precipitation Prediction Using SVM and Decision Trees
14. Joseph Kiwuuwa Balikuddembe (2021) Comparative evaluation of Naive bayes and k–nearest neighbor Classifiers to Improve Prediction of Short Term Precipitation
15. Joel Eyamu (2020) Computational Prediction of Multi-drug resistant Tuberculsois
16. Patrick Omara (2020) Multi-Risk Analysis of Prostate Cancer Survival
17. Allan Muhumuza Mutabazi (2019) Developing a low interaction Honeypot Detection System in a Networked Environment Using Live Environment and Network Analysis
18. Ibrahim Nuruddeen Isa (2019) Use of Satellite Imagery for Identification of Crop Lands, Types and Health
19. Yohannes D. Woldemichael (2018) A Data Analysis and Visualization Tool for Road User Survey Data
20. Francis Kamuganga (2018) Computational Statistical Analysis of Academic Results
21. Linda Namayanja (2017) Application of BPM in the Improvement of Procurement Process in Government Organisations
Office Address
School of Computing and Information Sciences
Department of Computer Science
Block A, Level 3
