Skip Navigation LinksResearch-Groups Research Groups

Research Groups

Research Groups
The IFK conceptualises its activities around research groups. In 2020 the following five were founded.

Data Science Across Disciplines (DSAD)
Director: Professor Charis Harley (Engineering)

Data Science
Across Disciplines takes an interdisciplinary approach to both the application of data science and the sense-making theoretical frameworks that shape its development. DSAD supports the educational and intellectual growth of the field of data science by developing specialist educational programmes at the postgraduate level, to support student skills development and upskill current professionals. The DSAD’s cutting edge research is allied with close industry collaboration.

Webinars (2021):
Terence van Zyl  "A High-Level Overview of the Applications of Deep Learning-Based Forecasting in Finance", 22 February
Luke Machowski  "Robot of Robots – Hyperautomation for the 4IR", 29 March | Presentation Link
Enrique Zuazua – "Neural Differential Equations, Control and Machine Learning", 26 April | Presentation Link
Moulay Akhloufi  "Intelligence Applied Research at the Perception Robotics and Intelligent Machines (PRIME), Canada", 31 May | Presentation Link
Siddhartha Mishra  "Deep Learning and Computations of High-Dimensional Partial Differential Equations", 21 June |Slides.pdf | Presentation Link 
Marco Rossi  "Data Analysis and Predictive Maintenance with MATLAB and Simulink", 26 July |Slides.pdf | Presentation Link 

27 – 28 October 2021, Conference: Ethics and Explainability for Responsible Data Science (EE-RDS). More info Register

6 – 10 December 2021, PG Workshop: Remaking the World through Machine Learning. More Info 
2 – 9 December 2020, PG Workshop: Remaking the World through Machine Learning.

Short Learning Programmes:
September 2021, Data Science in Practice | More Info.pdf 

Postgraduate Degrees:
Ph.D. in Data Science (Faculty of Engineering and the Built Environment) – for more information contact Prof C. Harley ( 

PG Funding:
The DSI and CSIR invite applications under the DSI-CSIR Inter-Bursary Programme for students intending to complete full-time studies at any South African public universities under specific themes.
DSI-CSIR Inter-Bursary.pdf

The Future of Health (FoH)
Director: Professor Benjamin Smart (Philosophy)

The Future of Health Research Group takes an interdisciplinary approach to understanding humanity’s efforts to improve health and deal with sickness, in the conviction that gaining perspective will improve future medical and public health efforts. The group’s broad mandate includes philosophical, sociological, anthropological, and other disciplinary approaches, and covers clinical medicine, public health, epidemiology, biomedical research, and other health knowledges.

The Future of Diplomacy (FoD)
Director: Dr Oluwaseun Tella (Politics and International Relations)

The Future of Diplomacy research group seeks to promote the understanding of diplomacy, negotiation and statecraft in contemporary international politics. The group aims to support research in modern diplomatic practice by redefining diplomacy in contemporary and futuristic contexts in an increasingly complex and globalised world.

Green Futures (GF)
Director: Professor Brett Bennett (History)

Green Futures seeks to positively understand, appreciate and harness earth's plant life and the socio-ecosystems they interact with for the betterment of humanity and nature. Green Futures draws on a range of disciplines, not limited to science, and has a strong grounding in culture, history, and policy.

Metaphysics and Machines (MnM)
Director: Professor Alex Broadbent (Philosophy)

Artificial intelligence is altering how we under
stand the world. The Metaphysics and Machines Research Group explores the implications, including how the approach of developing machine learning solutions changes or deviates from traditional scientific methodologies, whether such new approaches can help develop new or alternative conceptual frameworks, whether machine learning can improve our grasp of complexity, and what we can learn about the relationship between prediction, explanation and causation.