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Connect with our 40+ researchers in Management and Data science. Explore the opportunities for research collaborations, business innovation and media inquiries.

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Find the grants and job opportunities offered by MagIC, permanently updated.

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MagIC is a dynamic research center dedicated to advancing the field of Information Management through an interdisciplinary approach that combines Management and Data Science. Our goal is to develop innovative solutions and tools to enhance decision-making and benefit individuals, organizations, and society as a whole.

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  • IMAGEM MAGIC Noticia Card

    Discover the MagIC Journey: our Five-Year Activity Report

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  • Cardnoticias (002)

    Call for expression of interest: Marie Curie Postdoctoral Fellowships @ MagIC

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  • PROGRESSE Project On Business Investment Impact Bruno Damasio

    NOVA IMS Leads PROGRESSE Project on Business Investment Impact

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Key impact areas

Smart Cities
Tourism and Hospitality
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Our data-driven approaches improve diagnostic accuracy, personalize treatment strategies, and enhance patient care across medical domains. We develop innovative solutions for managing chronic diseases, predicting mortality, and contributing to mobile health, electronic health portals, and video consultations.
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Our research analyses complex combinations of large datasets in areas of public interest, namely Micromobility, Parking, Pollution, and Emergency. We have developed a pilot-scale digital smart city platform for urban modelling and planning, and an IoT-based system to facilitate Pay-As-You-Throw and recycling reward schemes.
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Our research deepens the understanding of sustainable technologies and energy communities, developing strategies and toolkits for emerging ST and energy communities and solutions for improving the quality of life in urban environments. We promote energy citizenship, allowing citizens to take control of their path to sustainability.
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Our research uses Data Science to analyse trends in hospitality and tourism, exploring social influence, technology within sharing economy platforms, and customer acceptance of AI-based services. We address the challenges and opportunities in an increasingly digital landscape.
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Our research sheds light on the most important antecedents and outcomes of e-learning technologies and identifies the main drivers and barriers for academic achievement in high schools. We develop innovative data-driven approaches, apply machine learning techniques for timely prediction of student performance, and conduct exploratory analyses of higher education census data. We also contribute to the area of education by finding the main determinants of e-learning systems' success.