Robotics, Autonomous Intelligence and Learning (RAIL)

The RAIL Lab at the University of the Witwatersrand is a research group focusing on Artificial Intelligence, Machine Learning, and Robotics.

The group's major focus is Reinforcement Learning (RL), both in terms of contributing the general development of the field as well as its applicability to a number of problem areas.

Other research areas include computer vision and theory of deep networks. Some of the application areas are healthcare and education.

As artificial intelligence (AI) systems become increasingly intricate, their decision-making processes, though remarkably accurate, often remain opaque and are often described as "black boxes."

This black box nature can prevent users from trusting or using them for problems where there are strong ethical considerations, such as in healthcare, finance, education, and public policy. In these applications, AI's decisions can profoundly impact individual lives and societal trajectories.

Without a clear understanding of how AI systems reach their conclusions, there is a risk that they will be underutilized or, worse, misapplied.

The WITS ExplainableAI Lab (EAI) endeavours to make the complex workings of AI systems transparent, interpretable, and trustworthy. The EAI lab has two main objectives.

• The first objective is to advance fundamental explainable modelling approaches. This is to provide a robust framework for understanding the underlying relationships and dependencies in data, offering clear insights into the 'how' and 'why' of AI decisions, and producing systems that "know when they don’t know."
• The second objective is to transform "black-box" models into transparent systems through post-hoc explainability, making the inner workings and decisions of these black-box models comprehensible and interpretable.

Director: Professor Ritesh Ajoodha

Mathematics in Industry Study Group

The Mathematics in Industry Study Group is a one week workshop where leading academics and top students from Universities across South Africa and abroad, meet and work in groups to solve real-world industry problems. Organisations and corporate companies are encouraged to submit problems that are of current importance to South African industry.

The Study Group participants employ a wide variety of techniques such as programming, mathematical modelling, and big data analysis, to develop creative solutions to these real-world problems which ultimately contribute to the development of South Africa.