Centres, Labs & Chairs

The School for Data Science and Computational Thinking works closely with several specialised centres, labs and industry chairs at Stellenbosch University. Together they apply data science, AI and computational modelling to real-world problems in health, policy, finance and beyond.

CERI SACEMA Policy Innovation Lab Standard Bank Lab Capitec Chair

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Centre for Epidemic Response and Innovation (CERI)

Tracking infectious disease outbreaks using large-scale genomic data to support public health responses through variant detection and real-time data sharing.

🌍 Genomic Surveillance Monitoring viral evolution and variants in real-time across the continent.

🏥 Public Health Translating complex data into actionable intelligence for health policymakers.

🎓 Capacity Building Training the next generation of African genomic scientists and bioinformaticians.

🤝 Global Partnerships Collaborating with the WHO and Africa CDC to strengthen health systems.

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SACEMA

South African Centre for Epidemiological Modelling and Analysis

Disease Modelling Building mathematical models to simulate disease transmission dynamics and evaluate control strategies.

Policy Support Supporting national health departments with evidence-based policy through rigorous quantitative analysis.

Interdisciplinary Integration Integrating data science, mathematics, and biology to improve health outcomes across Africa.

Mentorship & Training Training and mentoring new researchers in epidemiological modelling and analysis.

Policy Innovation Lab

Bridging the gap between data science and public policy through ethical, evidence-based solutions for the public sector.

⚖️ Ethical AI Tools Designing AI tools to support ethical, evidence-based policy decisions.

🏛️ Public Sector Integration Partnering with government to integrate data-driven approaches into workflows.

🌍 Responsible AI Advancing responsible AI aligned with the UN Sustainable Development Goals.

🎓 Digital Capacity Promoting capacity-building through workshops and research projects.

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Standard Bank Lab for Recommender Systems

Focus: Recommender Systems & Behavioural Analytics

➔Personalisation Algorithms: Developing tools that personalise user experiences using behavioural data.

➔Applied AI: Deploying machine learning in finance, mobility, and customer analytics.

➔Innovation Events: Hosting hackathons and challenge-based data science projects.

➔Industry Bridge: Building links between academia and corporate partners through applied research.

Capitec Chair in Applied AI

Leading the development of complex AI techniques for high-dimensional datasets, bridging the gap between academic theory and real-world financial technology.

Research Innovation

Developing novel machine learning algorithms for credit scoring, fraud detection, and customer behaviour analysis.

Social Impact

Applying financial AI techniques to health and social data to solve complex societal problems.

Talent Pipeline

Training a cohort of Masters and PhD students equipped with ethical, industry-ready AI skills.