Resource Registry: Research Entities

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.

Health care systems are under increasing pressure to cope with shifting demographics, the threat of chronic and non-communicable disease, pandemics, and rising health care costs. The uptake of innovations and technologies to meet these challenges and to advance medicine and health care delivery is not as rapid as the pace of change. Due to this challenge and pace of change, the University of Johannesburg (UJ) has mandated remarkable strides towards the fourth industrial revolution (4IR) activities and imperatives. In doing so, and in alignment with the GES 4.0, it is envisaged that the proposed Biomedical Engineering and Healthcare Technology (BEAHT) Research Centre will be the benchmark and hub for healthcare technology and innovative success.

The newly established (2022) Centre for Applied Data Science (CADS) within the School of Consumer Intelligence and Information Systems (SCiiS) represents the multidisciplinary efforts in the College of Business and Economics (CBE) at the University of Johannesburg. To provide evidence-based insights that unearth new oppurtunities and pathways that continually shape our student and staff experiences; our organisations, communities and society.

CADS has their sight set on becoming the leading Centre for applied data science in Africa, producing outstanding insights, research, learning programmes and delivering outstanding value for their stakeholders, partners, and collaborators.

The Computational Intelligence Research Group (CIRG) focuses on various aspects of fundamental and applied computational intelligence and machine learning research. Nature-inspired algorithms such as artificial neural networks, deep learning methods, self-organizing maps, particle swarm optimization and evolutionary computing are studied both theoretically and practically. Real-life applications include computer vision, data mining and anomaly detection.

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.

Our general areas of work straddle Data Science for Society as well as Local Language Natural Language Processing. These two strands are complementary. Our work in Data Science and Society has allowed us to have a more nuanced approach to understanding the systematic challenges that face being able to do excellent science with local languages. Through Data Science for Society, we have to understand how when one carries through Data Science research, we situate how the users are part of the process. We find that we need to adjust our research to take care of these challenges and innovate in ways we gather direct data or alternative data.

For us, Data Science for Society means being able to improve approaches/methods or scientific tools for DS while enhancing the ways decision-makers can use the insights that come from these tools. Local Language Natural Language Processing is focused on ways to develop new tools, new data and methodology to improve the state of African languages.

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 DigiForS research group undertakes research in Digital Forensic Science. DigiForS’s main objective is to find innovative security solutions for state-of-the-art technologies. This includes finding solutions that will help to make emerging technologies safe for use, using security technologies to enable new applications, find solutions that will better protect existing technology, as well as extracting forensically relevant information.

One of the strategic thrusts of the University of Johannesburg (UJ) is to lead Africa into the Fourth Industrial Revolution. The Institute for Intelligent Systems (IIS) was established in 2016 within the University of Johannesburg to act as a catalyst towards the UJ strategy for Global Excellence and Stature (GES). IIS is one of UJ’s flagship institutes for Global Excellence and Stature (GES 4.0).

The Machine Intelligence and Neural Discovery Institute (The Wits MIND Institute) at Wits University is an African-based interdisciplinary AI research hub that pushes the frontiers of scientific understanding of machine, human and animal intelligence. 

The Wits MIND Institute focuses on fundamental AI research that promotes breakthrough scientific discoveries and aims to grow a much-needed critical mass of AI expertise on the continent. Through robust interdisciplinary collaborations, MIND partners with industry and others to develop cutting-edge technologies tailored to Africa’s unique challenges.

The Wits MIND Institute also addresses how AI interfaces with society from an ethical and policy perspective, shaping governance and ensuring that AI development is safe, inclusive, and beneficial to all.