graduated from the inaugural Master of Climate Change program at the University of Waterloo and he is now working towards his PhD. For his doctoral research, Kurniawan is seeking to advance the methodological approach for better anticipating hard-to-foresee scenarios for complex social systems. Complex systems have many moving parts, where multiple opportunities exist for things to ‘go wrong’ simultaneously at different scales. Internal feedback mechanisms may encourage such cascading failures, making them more frequent than probability theory suggests. Through his work in multi-scales scenario research, Kurniawan has developed a keen interest in risk assessment and horizon scanning (RAHS) system architecture. Kurniawan believes his current research in matrix-driven scenario method has the potential to be extended as a provision for big data analytic platform for RAHS. The matrix is flexible and extendable that can incorporate various sub-functions such as environmental scanning, decision modelling, scenario analysis, Monte Carlo simulation, policy impact and sensitivity analysis, multiple levels and multiple sectors. Kurniawan has been involved in several scenario projects such as the Future of Urban Transport at the Singapore University of Technology and Design, the Future of Work/Technology 2050 for a global foresight think tank, the Millennium Project, and Canada’s Low-carbon Energy Futures for the Energy Council of Canada.