Artificial Intelligence, Machine Learning, Spatial-Temporal Data Analyses
Terence van Zyl holds the Nedbank Research and Innovation Chair at the University of Johannesburg where he is a Professor in the Institute for Intelligent Systems. He is an NRF rated scientist who received his PhD and MSc in Computer Science from the University of Johannesburg for his thesis on agent-based complex adaptive systems. He has over 15 years of experience researching and innovating large scale streaming analytics systems for government and industry. He has previously served South Africa as a sub-chair within the committee on earth observation satellites and as part of the South African delegation to the GEO Ministerial. He has received numerous awards including the Meraka Institute innovation excellence award, Council for Scientific and Industrial Research (CSIR) einstein special award and IEEE committee on earth observation medal for meritorious service. His research interests include data-driven science and engineering, prescriptive analytics, machine learning, meta-heuristic optimisation, complex adaptive systems, high-performance computing, and artificial intelligence.
Paskaramoorthy, A.B; Gebbie, T.J. and van Zyl, T.L. (2020) "A framework for online investment decisions", Investment Analysts Journal, 49 (3), p.215-231
van Zyl, T.L.; Celik, T. (2021) "Did We Produce More Waste During the COVID-19 Lockdowns? A Remote Sensing Approach to Landfill Change Analysis", IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, p.7349-7358
Dlamini, N.; van Zyl, T.L. (2021) "Comparing Class-Aware and Pairwise Loss Functions for Deep Metric Learning in Wildlife Re-Identification" Sensors, 21 (18), p.6109