Giulio Mattioli

Research Fellow, University of Leeds

Giulio Mattioli

Dr. Giulio Mattioli researches in the interdisciplinary area of Transport Studies. His research examines the multiple ways in which transport systems are locked into high (and increasing) levels of energy consumption and carbon emissions. He is specifically interested in developing a comprehensive understanding of car dependence, its social drivers and consequences, notably in terms of social inequalities. His research at SRI focuses on the political economy of social and technical provisioning systems in the transport sector, as part of the “Living Well Within Limits” (LiLi) project led by Dr. Julia Steinberger.

Dr Mattioli has a shared position between SRI and the Institute for Transport Studies at the University of Leeds, where he has been a Research Fellow since 2014, leading the EPSRC-funded project (t)ERES (“Energy-related economic stress in the UK, at the interface between transport, housing and fuel poverty”). He has held previous postdoctoral positions at the University of Aberdeen, working for the End Use Energy Demand (EUED) research centre DEMAND (Dynamics of Energy, Mobility and Demand). He obtained his PhD in Urban and local European Studies from the University of Milan-Bicocca. He has published over 10 internationally peer-reviewed articles since 2013 in journals including Transportation Research Part A, Transport Policy, Transportation, and the International Journal of Sustainable Transportation.

Twitter: @giulio.mattioli

PhD, Urban and Local European Studies (URBEUR), University of Milan-Bicocca, 2013 [Visiting PhD Student at Department of Sociology, Lancaster University & Chair of Integrated Transport Planning (IVP), Berlin Institute of Technology, 2011-2012]
MSc (Hons) Sociology, University of Milan-Bicocca, 2009
BSc (Hons) Sociology, University of Milan-Bicocca, 2006

Research Interests
Car dependence & carbon lock-in in the transport sector
The political economy of transport systems
Transport poverty & affordability
Quantitative analysis of household social survey data