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Machine learning for cohort-based high-resolution spatial population projections Marina Georgati, Aalborg University CPH Abstract Cities expand rapidly with international migration significantly contributing to urban growth and urban population change. However, cities miss out on a great opportunity of reclaiming valuable knowledge on future population distribution due to the lack of established tools and methodologies to […] |
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Revealing the determinants of gender inequality in urban cycling with large-scale data by Rossano Schifanella, Associate Professor in Computer Science at the University of Turin. Abstract Cycling is an outdoor activity with massive health benefits and an effective solution for sustainable urban transport. Despite these benefits and the recent rising popularity of cycling, most countries still have […] |
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The Nordic research councils in the Humanities and Social Sciences have provided generous funding to establish the Nordic Network for Science of Science and to run a series of workshops about the latest research on the science of science, focusing on the research scene within the nordic countries. Roberta is giving a keynote at the […] |
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Establishing a quantitative science of bicycle networks Making transportation in cities sustainable is one major key to solving the climate, urban livability, and urban transport crises. To this end, urban data science offers new tools to quantify societal problems in cities and to guide policy makers with human-centric solutions. In this talk I outline our […] |
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