Cristina Oliveira

MagIC is an interdisciplinary research centre at NOVA Information Management School (NOVA IMS), Universidade NOVA de Lisboa, bringing together Management and Data Science to address complex societal and economic challenges through data-driven research and innovation.

Our distinctive strength lies in bridging advanced data science methodologies with management expertise and real-world needs, transforming data and scientific knowledge into actionable insights, innovative solutions, and evidence-based decision-making tools for businesses, public authorities, and other non-academic stakeholders.

MagIC's research spans areas such as artificial intelligence, machine learning, deep learning, evolutionary computation, synthetic data generation, and geoinformatics, combined with expertise in information systems, marketing, finance and risk management, and public policy.

Our interdisciplinary research is organised around five key societal impact areas:

• Health: Advancing data-driven approaches to healthcare, disease prevention, health management, and decision support.

• Smart Cities: Supporting smarter urban planning, mobility, public services, and sustainable territorial development through advanced analytics and geospatial intelligence.

• Sustainability: Developing data-driven solutions to environmental, economic, and social sustainability challenges, including resource management and climate-related decision-making.

• Tourism and Hospitality: Leveraging data science to understand visitor behaviour, improve destination management, and promote sustainable and competitive tourism ecosystems.

• Education: Applying analytics and artificial intelligence to improve learning experiences, educational management, and evidence-based educational policies.

Our contribution to Excellence Hubs

MagIC is particularly interested in joining interdisciplinary, cross-sectoral innovation ecosystems that connect universities, businesses, public authorities, and civil society organisations to address shared regional and European challenges.

We can contribute through advanced data science and AI expertise, interdisciplinary research, co-development of data-driven solutions with non-academic partners, knowledge transfer, and the translation of research outcomes into practical applications.

Our ambition is to help strengthen innovation ecosystems by making advanced data science accessible, relevant, and actionable for stakeholders, supporting research-driven innovation, informed decision-making, and sustainable societal and economic impact.