CSIR Modelling and Digital Science
The ever-increasing complexity of engineered and natural systems that have become part of our lives requires a multidisciplinary approach in which computational science is key for:
- Modelling and simulation, required for us to fully understand and monitor our systems; and
- Development of new algorithms to solve complex problems and optimisation techniques required to increase efficiency thereof.
CSIR Modelling and Digital Science develops capabilities in computational science applied in a variety of focus areas, through encouraging cross-pollination of computational science across domains. Specifically, the unit applies these capabilities in the space of information security, mathematical modelling, Data Science and mobile intelligent autonomous systems.
Focus on Information security – The Information security competency develops novel solutions in identity authentication through research on biometrics and token-based systems; and contribute solutions for monitoring and assessment of security in the cyber space through research on network penetration testing, intrusion detection and forensics.
Focus on Mathematical modelling – CSIR mathematical modellers apply their skills in domains such as the natural environment, to support research in areas such as coastal engineering and climate modelling; the engineered environment, to support research in areas such as rail engineering, aeronautics and roads design; and the resource and behavioural domains, to support research in areas such as water and energy demand modelling, and human behaviour predictive analytics, for example in voting predictions.
Focus on Mobile intelligent autonomous systems – The mobile intelligent autonomous systems laboratory focusses on the research and design of field robots that are deployable in areas hazardous for human beings to navigate, in automated product or infrastructure inspection as well as search and rescue missions
Focus on Data Science – MDS primarily undertakes Data Science initiatives for social good. Data Science is primarily an enabler for state or private entities to plan, gain insight into processes and associated behaviours; and to take appropriate actions or make informed decisions. Data Science can be leveraged as a potential solution for collecting and mining information from a whole host of sources (documents, databases, etc.) in order to enable fusion, learning, correlating, qualifying and quantifying multiple contributions towards a specific goal or target.