Personal profile
Research Interests
Developing and applying intelligent (or AI-based) systems for cost-effective real-time monitoring, asset health diagnosis, demand forecasting, predictive maintenance, and anomaly detection. His application areas of interest include ambient water quality, drinking water plants, wastewater treatment plants, and industrial plants such as coal-fired power stations.
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):
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SDG 3 Good Health and Well-being -
SDG 4 Quality Education -
SDG 6 Clean Water and Sanitation -
SDG 8 Decent Work and Economic Growth -
SDG 9 Industry, Innovation, and Infrastructure -
SDG 11 Sustainable Cities and Communities -
SDG 12 Responsible Consumption and Production -
SDG 13 Climate Action -
SDG 14 Life Below Water -
SDG 17 Partnerships for the Goals
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Dive into the research topics where Thulane Paepae is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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An explainable ensemble machine learning approach for multi-domain, multiclass sentiment analysis in Amazon product reviews
Mokgwatjane, K. & Paepae, T., Mar 2026, In: Machine Learning with Applications. 23, 100825.Research output: Contribution to journal › Article › peer-review
Open Access -
Fabrication of a multijunction nitride-based Ti1.33N@BiVO4/GdIn2Se3 MXene heterostructure with enhanced optoelectronic and photoelectrochemical properties
Malati, M., Thango, B., Paepae, T., Gule, N. & Dlamini, L., Jan 2026, In: Applied Surface Science Advances. 31, 100921.Research output: Contribution to journal › Article › peer-review
Open Access -
Advancing SDG 6.3.2 with machine learning-based virtual sensors for high-frequency nutrient monitoring
Ngwenya, B., Paepae, T. & Bokoro, P. N., Nov 2025, In: Journal of Water Process Engineering. 79, 108831.Research output: Contribution to journal › Article › peer-review
Open Access1 Citation (Scopus) -
Berth Allocation and Quay Crane Scheduling in Port Operations: A Systematic Review
Makhado, N., Paepae, T., Sejeso, M. & Harley, C., Jul 2025, In: Journal of Marine Science and Engineering. 13, 7, 1339.Research output: Contribution to journal › Review article › peer-review
Open Access4 Citations (Scopus) -
Monitoring ambient water quality using machine learning and IoT: A review and recommendations for advancing SDG indicator 6.3.2
Ngwenya, B., Paepae, T. & Bokoro, P. N., May 2025, In: Journal of Water Process Engineering. 73, 107664.Research output: Contribution to journal › Review article › peer-review
Open Access9 Citations (Scopus)
Press/Media
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Pnet Report warns of growing software developer shortage in South Africa
19/01/26
1 item of Media coverage
Press/Media
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South Africa’s maths pipeline is collapsing – and the economy will pay
14/01/26
3 items of Media coverage
Press/Media