Find Academic Supervisors

• Complex and Dynamic Systems
• Computer Networks
• Networked Multimedia Systems
• +11 more

Rui J. Lopes is an Associate Professor in the Department of Information Science and Technology at ISCTE – Instituto Universitário de Lisboa, where he has been a faculty member since 1997. He is also an Integrated Researcher and Coordinator of the Network Architecture and Protocols Group at the Institute of Telecommunications - IUL. He holds a PhD in Computer Science from Lancaster University (2005), a Master’s and Bachelor’s in Electrical and Computer Engineering from Instituto Superior Técnico, University of Lisbon. PhD in Computer Science – University of Lancaster (2005) Master’s in Electrical and Computer Engineering – Instituto Superior Técnico (1997) Bachelor’s in Electrical and Computer Engineering – Instituto Superior Técnico (1994) His research focuses on complex and dynamic systems, particularly multilayer hypernetworks, networked multimedia, and applications in sports performance analysis. He has made significant contributions to modeling team synergies in football using network science and optical tracking data. His work bridges computer science, network theory, and sports analytics, with a strong emphasis on real-world applications. His recent publications span high-impact journals in sports science, network science, and complex systems. Key themes include team coordination, temporal networks, performance modeling, and the application of information theory to sports. His research often integrates data-driven modeling with theoretical frameworks to uncover patterns in collective behavior. Guest Editorial: Advances in Tools, Techniques and Practices for Multimedia QoE (2015) Multiple publications in Sensors, Chaos, Solitons & Fractals, European Journal of Sport Science, and Sports Medicine High citation counts across Google Scholar (598), Scopus (282), and Web of Science (269) Rui J. Lopes has supervised over a dozen master’s students and five PhD candidates, three of whom completed with the highest grade. He has also contributed to academic leadership by directing the doctoral program in Complexity Sciences (2018–2020) and promoting internationalization programs such as Erasmus and IAESTE. His research is conducted primarily at the Institute of Telecommunications, where he leads a research group focused on network architectures and protocols. He is actively involved in interdisciplinary research, collaborating with experts in sports science, urban planning, and social systems. His work on syntgen, a system for generating temporal networks, and on protest modeling using agent-based simulations, highlights the breadth of his methodological expertise.

• Network Science
• Data Science
• Machine Learning
• +3 more

Luis Ramada Pereira is an Associate Researcher at ISTAR-Iscte Research Center and Visiting Professor at ISCTE-IUL. He holds a PhD in Complexity Sciences from ISCTE-IUL/University of Lisbon and has extensive industry experience at IBM managing multinational tech projects. Research Focus: His work centers on Network Science applications, including: Temporal network modeling Machine learning for complex systems Information-theoretic analysis of sports dynamics Computational frameworks for network generation Publication Trends: Recent articles demonstrate a consistent focus on sports analytics (particularly football) through network science lenses, with publications in Q1 journals like Chaos, Solitons and Fractals . Research methodologies emphasize information theory, temporal clustering, and multilayer network modeling. Teaching: Data Structures and Algorithms (2019/2020) Programming Fundamentals (2019/2020) Data in Science, Management and Society (2019/2020)

• Computational Physics
• Materials Science
• Social Network Analysis
• +6 more

Marco Buongiorno Nardelli is a University Distinguished Research Professor in the Department of Physics at the University of North Texas. He is affiliated with the Initiative for Advanced Research in Technology and the Arts (iARTA) and the Center for Experimental Music and Intermedia (CEMI). His work bridges computational physics, materials science, and artistic research through concepts like "music as data, data as music." His research spans: Design of novel materials for renewable energy and nanoelectronics Advanced electronic structure theories Complex systems and social network dynamics Topological data analysis and quantum walks Music theory and computational media art His recent publications focus on opinion dynamics, network science, and interdisciplinary applications of physics to social and biological systems, showing strong connections between computational methods and real-world phenomena. Scientific recognition includes: Fellow of the American Physical Society Fellow of the Institute of Physics His interdisciplinary approach has influenced both scientific and artistic communities through collaborations with iARTA, CEMI, and Parma Recordings, while his research integrates materials genomics, social dynamics, and data ethics.

Zachary NealView profile

Professor

• Network Science
• Social Networks
• Computational Social Science
• +7 more

Zachary Neal is a Professor in the Department of Psychology at Michigan State University , affiliated with the Social-Personality program. He is an active researcher in network science, with interdisciplinary work spanning psychology, sociology, education, and geography. He serves as editor of Global Networks and promotes open science through initiatives like the Recommendations for Sharing Network Data and Materials. Position: Professor Institution: Michigan State University Department: Psychology School: College of Social Science Email: zpneal@msu.edu Website: www.zacharyneal.com Bluesky: @zpneal.bsky.social His research focuses on networks , particularly ego networks, two-mode networks, and cognitive social structures. He emphasizes methodological rigor, open data practices, and the use of R for network analysis. He is also known for his work on childfree identity and public scholarship. The most recent publications reflect a strong commitment to open science, data sharing standards, network pedagogy, and interdisciplinary collaboration . Themes include network visualization (e.g., 'nutrition labels'), higher-order networks, and the social dynamics of research communities. His work bridges theoretical network science with practical applications in health, education, and policy. Scientific Recognition: SIPS 2025 Commendation for Recommendations for Sharing Network Data and Materials Editor, Global Networks Organizer of teaching initiatives in network science Zachary Neal is actively involved in mentoring students, promoting best practices in research, and securing collaborative grants related to network science and open scholarship. He contributes to the academic community through conference organization (e.g., Sunbelt), editorial work, and public engagement on social media. He leads research initiatives that often involve cross-institutional teams and open-source tools. He is associated with research groups and labs focused on computational social science, network analysis, and open research practices . His work on the Moral Minds Lab (via affiliation) and independent projects indicates leadership in teams that study social cognition and behavior through network lenses. Future work is likely to expand on data sharing frameworks, network teaching tools, and the social implications of network structures in diverse contexts.