Meead holds a PhD degree in transportation systems analysis and planning from Northwestern University, USA. He also has a Master's and a Bachelor degree in Civil Engineering.
He leads the CityX research lab as part of the School’s Research Centre for Integrated Transport Innovation (rCITI). The Lab focuses on scientific understanding of cities through modelling, simulation, data analytics, and visualisation.
Meead views transport systems as networks. His research mostly focuses on understanding the characteristics and modelling the dynamics of the transport networks with an overarching aim to mitigate urban traffic congestion and improve urban liveability. His research outcomes allow a more efficient management and control of transport networks in cities that could potentially save millions of dollars in avoidable social and environmental cost of congestion and will improve people’s quality of life.
The impact of his research is demonstrated by the growing engagement with major industry partners such as Cisco and Mitsubishi Heavy Industries as well as a number of local and state government agencies including the City of Sydney, City of Willoughby and Transport for NSW.
One of Meead’s recent research projects showed that 70% of the Indigenous population in the City of Sydney live in neighbourhoods with lower-than-average walkability. Reducing transport inequality and improving walkability in Indigenous communities are necessary to help close the health and social gap. Meead has also worked closely with Transport for NSW to develop machine learning based models to predict walking and cycling volumes across Sydney metropolitan area.
Meead is a member of the traffic flow theory and characteristics committee of the Transportation Research Board of the U.S. National Academies. He is an Associate Editor of the Journal of Big Data Analytics in Transportation and an editorial board member of the Journal of Advanced Transportation and Journal of Transportation Letters.
He is also a co-founder of a UNSW spinout company footpath.ai that aims to make the world a more walkable place. The startup focuses on collecting footpath-level imagery data and turning it into artificial intelligence (AI) powered insights for a range of applications to improve walkability and localisation for autonomous delivery robots in cities.