Anban Pillay
Anban Pillay is a University of KwaZulu-Natal computer scientist whose AI research spans language processing, agricultural decision systems and quantum machine learning. He began teaching Computer Science at UKZN in 2000, joined the organising team for its Deep Learning IndabaX in 2019 and co-supervised a 2020 study of isiZulu word-sense disambiguation. His work includes a 2022 decision model for sugarcane growers and two 2023 studies of quantum machine learning, one on pulsar classification and one on quantum feature-map design. In May 2025, he co-supervised deep-learning research on accent recognition; as of October 2026, he is a Senior Lecturer at UKZN’s Centre for Quantum Computing and Technology and coordinates the UKZN node of the Centre for Artificial Intelligence Research.
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Timeline
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Since 2000
Computer Science teaching
Since 2000, he teaches several Computer Science courses at UKZN.
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2019
Organising Deep Learning IndabaX
In 2019, he joins UKZN’s organising team for a three-day Deep Learning IndabaX at its UNITE Building. Researchers, students and machine-learning experts from across Africa attend the event.
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2020
IsiZulu word-sense disambiguation
At UKZN, he co-supervises Sibonelo Dlamini’s 2020 master’s project on isiZulu language processing. Dlamini tests whether information about word structure improves word-sense disambiguation in isiZulu.
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2022
Sugarcane decision agents
In 2022, he coauthors a paper that enhances a Belief-Desire-Intention (BDI) architecture with a dynamic decision network to model sugarcane growers’ daily decisions. The model accounts for uncertain weather forecasts, cane dryness, emergencies and unexpected mill requests for different cane amounts.
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2023
Quantum classifiers for pulsars
In 2023, he coauthors a study evaluating ensembles of single-qubit QAUM classifiers with classical bagging and boosting. It reports improved validation accuracy for pulsar classification.
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2023
Quantum feature-map design
A separate 2023 paper he coauthors uses kernel-target alignment as a faster substitute for accuracy in genetic-algorithm design of quantum feature maps. It compares eight new approaches with the original across nine binary classification problems.
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May 2025
Accent recognition research
In May 2025, he co-supervises Yuvika Singh’s MSc research on accent recognition using deep learning. The project identifies a speaker’s home language from their accent, then switches to an accent-specific speech recogniser.
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As of October 2026
Senior Lecturer at UKZN
As of October 2026, he is a Senior Lecturer at UKZN’s Centre for Quantum Computing and Technology and coordinates the UKZN node of the Centre for Artificial Intelligence Research. His listed qualifications include an MSc and BSc Honours in Computer Science, a Diploma in Datametrics and a B.Paed in Science. CAIR@UKZN studies machine learning and deep learning, including deep-learning neural-network and Bayesian deep-learning methods for recommender systems, natural language processing, self-driving cars, image processing and computer vision.
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Sources and credits
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- Pillay Anban - Agriculture and Science
- UKZN Hosts Deep Learning IndabaX - College of Agriculture, Engineering and Science
- Master’s Research Paves Way for IsiZulu Language Processing - College of Agriculture, Engineering and Science
- An adaptive, probabilistic, cognitive agent architecture for modelling sugarcane growers’ operational decision-making
- Classical Ensembles of Single-Qubit Quantum Variational Circuits for Classification
- Hybrid Genetic Optimisation for Quantum Feature Map Design
- Master’s Graduate Focuses on Accent Recognition Using Deep Learning - Agriculture and Science
- Team - Centre for Quantum Computing and Technology
- Research Groups | CAIR