Tiago P. Peixoto received his habilitation in theoretical physics at the University of Bremen in 2017. Previously, he was Full Professor at IT:U (2024-2026), Associate Professor at the Central European University (2019-2024), Assistant Professor in Applied Mathematics at the University of Bath (2016-2019), External Researcher at the ISI Foundation (2015-2020), and post-doc researcher at the University of Bremen (2011-2016) and Technical University of Darmstadt (2008-2011).

He received his PhD in Physics at the University of São Paulo in 2008.

Organisms, ecosystems, climates, information systems, and societies are examples of complex systems: they exhibit rich behavior emerging from a large number of individual components following relatively simple local rules, based on a network of direct interactions.

Complexity science is traditionally devoted to solving the forward problem: Given postulated local rules of interaction, what is the large-scale organization that emerges from them?

Our research group focuses on the inverse problem: Given an empirically observed large-scale organization, what are the local rules of interaction that caused it?

With this aim, our group develops mathematical and computational models to explain the structure and function of complex network systems, and the algorithms to reconstruct the structure of these models from available empirical data.

We are particularly interested in problems related to:

1. Statistically principled pattern identification in complex networks.
2. Inverse problems and reconstruction of large-scale systems from indirect data.
3. Uncertainty quantification for complex systems.
4. Generative models that characterize modular hierarchies, ranks, and latent spaces.
5. Temporality, higher-order organization, and multivariate annotation of relational data.
6. Scalable network algorithms.
7. Scientific software development and dataset curation.

In our work, we employ theory and methods from several disciplines, including statistical physics, computational statistics, information theory, Bayesian inference, and machine learning.

For more information see our research and publications pages.

For more information see our publications page.

See here.

• Erdős–Rényi Prize (2019).
• Alexander von Humbolt Foundation fellowship (2008)
• 6th recipient of the distinguished Karate Club CLUB prize. 🥋🏆