Press Coverage



  • Smart city transport systems, A*STAR Press Coverage, 25 January 2017. [link]

  • Machine-learning to inspire Singapore metro buildout, United Press International, Inc., 25 January 2017. [link]

  • Machine-learning program predicts public transport use in Singapore,, 25 January 2017. [link]

  • Smart Data, Smart City, A*STAR Press Coverage, July 2016. [link]

  • A mathematical analysis of urban traffic models clarifies dispute over which approach is best, Science Daily, June 2016. [link]

  • How to reach disaster zone faster, A*STAR Television, July 2015. [link]

  • The right route to disaster relief, A*STAR Research,17 December 2014. [link]

  • A*STAR researchers develop predictive model for mass-transit train overloading, Green Car Congress, 24 November 2014. [link]

  • An agent-based model that analyzes commuters’ travel data will improve the Singapore rail experience, Asia Research News. [link]

  • Helping trains take the strain, Science Daily Featured Research, 21 November 2014. [link]

  • Computer model that can replicate the growth of cities has valuable implications for urban planning and sustainability, July 16, 2014. [link]

  • Network Science To Aid Disaster Relief Operations, Alan Aw, Asian Scientist, April 29, 2014. [link]

  • Mapping a tool to guide rescuers in disaster zones, David Ee, The Straits Times, April 30, 2014. [link]

  • Researchers propose network-based evaluation tool to assess relief operations feasibility, Science Daily Featured Research, April 16, 2014. [link]

  • Urban planning: City dynamics yield to computer modeling, Science Daily Featured Research, 11 September 2013. [link]

  • New computer model of city dynamics could pave way to planning sustainable urban areas,, 11 September 2013. [link]