Martina Contisciani

Center for Critical Computational Studies (C³S)

Goethe University Frankfurt

My research focuses on the development of statistical methods and algorithms to analyze complex systems, with a particular interest in network inference. I am also passionate in applying these methodologies to real-world problems and I am currently involved in the MOMA project, which aims to model the multiscale network structure of migration flows in Austria.

I completed a Ph.D. in Computer Science at the Max Planck Institute for Intelligent Systems and the University of Tübingen, supervised by Dr. Caterina De Bacco, with a doctoral dissertation entitled “Probabilistic Generative Models for Inference on Complex Systems”. My Ph.D. has been supported by the Cyber Valley and the International Max Planck Research School for Intelligent Systems (IMPRS-IS). I also hold a master’s degree in Data Science and a bachelor’s degree in Statistics for Business and Economics, both from the University of Padua.

For more details, check my CV.

news

Jun 26, 2026	Upcoming talks at BAYSM 2026 and the 2026 ISBA World Meeting. I will present the paper “Multiscale patterns of migration flows in Austria: regionalization, administrative barriers, and urban-rural divides” during the session “Bayesian methods in Causal Inference and Network Science” at BAYSM 2026 and the poster session at the 2026 ISBA World Meeting.
May 01, 2026	The Inverse Complexity Lab has moved to the Center for Critical Computational Studies (C³S) at Goethe University Frankfurt am Main, where I have started a new postdoctoral position.
Feb 26, 2026	Upcoming talks at the Vienna Workshop on Migration Modeling. Thomas Robiglio will give a presentation on the sociodemographic differences in Austrian migration networks, while my talk will be about the multiscale patterns of migration flows in Austria.