Dr. Nicolas Caradot is working since 2010 at Berlin Centre of Competence for Water (KWB), a leading R&D institute on urban water management. He is currently the head of a research group on smart city and infrastructure. He has contributed over the past years on numerous R&D projects on urban drainage monitoring, modelling and decision making. His main research area is the use of data, statistics and machine learning to better understand the behavior of urban networks and increase the rationality of decision making processes. He holds a PhD thesis on the topic of the simulation of sewer asset management strategies. He is now coordinating a European H2020 innovation project on digital water management called digital-water.city. Caradot chairs the UDAM working group on Urban Drainage Asset Management from the Joint Committee on Urban Drainage and he is a member of the Management Committee of the Specialist Group on Strategic Asset Management (SAM) from the International Water Association.
The potential of AI and machine learning for water management is immense and yet untapped. With increased data availability and interoperability, AI should help us to fully understand, predict and control the behavior of even the most complex systems.