Tran, Martino

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Research Interests

• Climate change
• Data science
• Technology
• Transportation
• Urban systems

Research Projects

• Population projections by age, sex, ethnicity, income, and education: We are developing high-resolution population projections for diverse demographic groups in Canada under the Shared Socioeconomic Pathways (SSPs) through 2100. Using a novel deep learning–based population dynamics model that predicts full population compositions while integrating macroeconomic, governance, and land-surface variables, we examine shifts in demographic proportions at national, regional, and local scales and highlight the effects of adaptation and mitigation challenges. By providing detailed, disaggregated population projections at fine spatial scales, this work supports policy interventions that more effectively target and prioritize vulnerable communities.
• Databases & High-Performance Computing for Urban Systems Research: As part of a next-generation urban analytics data management system, we are working on setting up some of the database and computing architecture for UPAL. This includes setting up computing resources to provide easily accessible, centralized, well-governed urban systems datasets that are structured for usability, and ensuring any software developed in the lab that relies on that data can easily be run in on the lab’s high-performance computing resources.
• Linking Urban Morphology to Socioeconomics Using Computer Vision and Deep Learning: Recent advancements in applied computer vision, such as the development of convolutional neural networks (CNNs), have transformed our understanding of how information is extracted from complex images. Furthermore, it has been shown that CNNs can disseminate unstructured, unclassified information within satellite images in order to predict socioeconomic features, such as poverty. At UPAL, we are building upon this recent body of work by applying CNNs to satellite images of urban centres in North America. Our goal is to answer questions such as: how does the complex structure of a city force inequity within the city? How has the growth of cities, or the dynamics of morphology, related to changes in socioeconomics, or the dynamics of liveability? What lessons can small, rapidly-growing cities learn from cities that grew rapidly in the preceding decades?
• Transportation Futures: The transportation sector in British Columbia is currently the single largest source of greenhouse gas (GHG) emissions in the province. The five-year Transportation Futures project, launched in 2015, brings together an interdisciplinary research team to help identify pathways for cleaner air, land and domestic marine transportation in B.C. and Canada. The project is hosted at UBC’s Clean Energy Research Centre (CERC), and supported by the Pacific Institute for Climate Solutions. Together with colleagues at the University of Victoria and Simon Fraser University, we are exploring how to build cleaner transportation through market and public policy, low and zero-carbon emissions infrastructures, and electric vehicles. We are developing new multi-criteria transport infrastructure optimization tools to inform a technology policy road-map for British Columbia.