Resource Registry: Data Science

This research group spans the University of Johannesburg with staff, students and postdoctoral researchers working in different areas that apply AI and Machine Learning. Their research areas include: Telecommunications, power-line communications, smart grid, and visible light communications, Machine learning, Artificial Intelligence, Data science, Renewable Energy, Power Systems, Power Engineering, Power Distribution and Generation.

The research group focuses on data-related research and development within a cross-disciplinary space. The research group aims to develop and advance methodologies, algorithms, tools and techniques in a holistic manner within the field of data science by working in the following areas: Data Wrangling, Data Mining, Data Analysis and Visualisation, Data Engineering, Data Science, Machine Learning Engineering, Fairness, Accuracy, Confidentiality, Transparency, Security (FACTS) and Discrimination in Data.

The Data Science Across Disciplines Research Group from the Faculty of Engineering and the Built Environment is pleased to offer a short learning programme on Data Science in Practice. Tools associated with the Fourth Industrial Revolution – such as Data Analysis, Machine Learning Modelling and Data Visualisation – are becoming increasingly critical in industry, making it imperative that staff upskill in the area of Data Science as a whole. The purpose of this programme is to provide professionals, from diverse backgrounds, with a solid knowledge base in the field of Data Science as required when tackling problems across social, economic and technical fields. This programme is ideal for early career professionals in need of upskilling to become Data Scientists as it offers the necessary theoretical knowledge and practical experience.

The Research Group on Data, Artificial Intelligence (AI), and Innovations for Digital Transformation was founded by Prof. Abejide Ade-Ibijola on April 1, 2022. The group is dedicated to advancing research and practical appli cations in data science, AI, and digital innovations, contributing to solving interdisciplinary challenges. Our research outputs include journal and conference publications, book chapters, patents, software applications, and commercialized products such as video games and mobile applications. The group also plays a crucial role in mentoring undergraduate and postgraduate students, and fostering industry collaborations.

The NICOG research group focuses on solving real-world problems using machine learning and optimisation techniques that take analogies from nature such as genetic algorithms and neural networks.