Associate Professor, Tier 2 CRC: Complexity and Sustainability
- Email: firstname.lastname@example.org
Martino is Associate Professor and Canada Research Chair (T2) in Computational Urban Science and Planning. He is also Principal Investigator of the Urban Predictive Analytics Lab that is broadly interested in the application of computational and data sciences for tackling urban planning challenges.
Martino has led both technical and policy research on the large-scale deployment of smart energy and transport technologies, and has worked with UNEP, UNDP, Hitachi Europe’s Smart Cities Program, and various municipal governments. He has lectured at UBC and Oxford on Sustainable Energy, Climate Change and Smart Cities.
Previously, he was Co-Director, Master of Engineering Leadership (MEL) in Urban Systems at UBC (2015 - 2018), Oxford Martin Fellow in Complexity, Resilience and Risk, University of Oxford (2013 - 2015), and Senior Research Fellow for the UK Infrastructure Transitions Research Consortium (2012 - 2014) where he contributed to the national infrastructure simulation platform now used by the UK government and the United Nations Engineering Branch (UNOPS). Martino completed his PhD in Environmental Science specializing in Computational Modelling at the University of Oxford, where he developed algorithmic behavioural models of social network influence to understand and predict early adoption of electric vehicles for climate change mitigation.
Martino's research focuses on understanding the environmental, societal and ethical implications of new data, technology and infrastructure in cities. He applies complexity sciences and computational methods to measure, characterize and model interdependencies between people, technology and the built environment to address the following research questions: Who benefits from new data and technology and what are the implications for equity and inclusiveness? What are the limitations and opportunities for technology to improve human well-being and mitigate climate change? How can scientific research inform policy and planning to achieve more positive sustainability outcomes?
- Master Engineering Leadership
Research and Specialties
- Climate change
- Data science
- Urban systems