Martina Contisciani

Martina Contisciani is a Research Fellow at the Department of Network and Data Science, Central European University (CEU), Vienna. Her work focuses on developing statistical methods and algorithms for analyzing complex systems, with expertise in network inference and multiscale modeling.

Her academic background includes:

• Ph.D. in Computer Science from Max Planck Institute for Intelligent Systems and University of Tübingen (2023), supervised by Dr. Caterina De Bacco
• M.Sc. in Data Science from University of Padua, Italy
• B.Sc. in Statistics for Business and Economics from University of Padua, Italy

Contisciani's research centers on network science, particularly probabilistic generative models for complex systems. She has pioneered work in community detection for multilayer and hypergraph networks, developed the Hypergraphx library for higher-order network analysis, and currently leads migration flow modeling in Austria through the MOMA project. Her methodological innovations bridge theoretical network science with real-world demographic applications.

Analysis of her 15 most recent publications (2017-2025) reveals an evolution from foundational work on community detection and network modeling toward impactful applications in migration studies. Her recent output demonstrates increasing integration of statistical inference with spatial and demographic data, particularly through multiscale network approaches applied to Austrian migration patterns.

Her scientific recognition includes:

• Cyber Valley PhD Fellowship
• IMPRS-IS Fellowship

Contisciani actively contributes to the MOMA project under Prof. Tiago P. Peixoto and Prof. Márton Karsai, developing inferential network models for migration analysis. While no formal student advising is documented, her role involves collaborative research within CEU's Network and Data Science department. Her recent presentations at IC2S2’25 and NetSci 2025 highlight ongoing contributions to network science methodology and applications.

As a core member of CEU's Network and Data Science research team, she collaborates with leading network scientists on projects combining theoretical innovation with societal challenges. Her current work on Austria's migration flows represents a strategic shift toward data-driven policy-relevant research while maintaining strong methodological rigor.