معرفی
Jorge Louçã is a Full Professor in the Department of Information Science and Technology at ISCTE-IUL, where he has been a faculty member since 2000. He is also an Integrated Researcher at ISTAR-Iscte, the Research Center in Information Sciences, Technologies and Architecture, and leads the research group The Observatorium. He holds a PhD in Computer Science and Artificial Intelligence from Université Paris Dauphine and the University of Lisbon, and completed his Aggregation in Complexity Sciences in 2019.
- PhD in Computing – University of Lisbon & Université Paris-Dauphine (2000)
- Master’s in Informatique: Intelligent Systems – Université Paris-Dauphine (1995)
- Aggregation in Complexity Sciences – ISCTE-IUL (2019)
His research centers on computational modeling of social systems, focusing on data-intensive analysis of human communication, knowledge generation in large networks, and the dynamics of complex systems. He founded the Doctoral Program in Complexity Sciences and has been instrumental in advancing the field through international collaborations such as the UNESCO Unitwin network for the Complex Systems Digital Campus and participation in the Conference on Complex Systems (CCS/ECCS).
The recent publications highlight a strong interdisciplinary focus, combining network science, data analysis, and social theory. Key themes include the modeling of malaria transmission, information diffusion in social media, structural inequality in education, and the dynamics of opinion and popularity. His work often employs agent-based models, temporal network analysis, and entropy-based measures, reflecting a deep integration of computational and theoretical approaches.
- Research Methods for Doctorate in Complexity Sciences
- Advanced Topics in Complexity Sciences
- Data Science Fundamentals
- Development for the Internet and Mobile Applications
- Web Interfaces for Data Management
- Advanced Network Analysis
Jorge Louçã has supervised over a dozen doctoral and master’s students, with completed theses on topics such as malaria modeling, information diffusion, temporal networks, and social inequality. His research has been supported by projects like NESS (Non-Equilibrium Social Science in ICT and Economics), reflecting his leadership in interdisciplinary science. He has held significant academic management roles, including Director of the Department of Information Science and Technology and head of multiple degree programs. His work continues to bridge computer science, social science, and policy, positioning him as a key figure in the global complexity science community.
