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:research groups
:research groups

Complex Systems and Network Science

:overview

Sina Sajjadi

PhD Student

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Sina Sajjadi

I am a Ph.D. candidate at the Inverse Complexity Lab at IT:U, collaborating with the Complexity Science Hub Vienna. My research focuses on complex systems, particularly the mathematical modeling of social phenomena through network science, statistical inference, game theory, and data analysis.

My current interests include inferring network structure from dynamics data, statistical inference of higher-order networks, exploring inequalities and disparities in networks, and studying homophily and segregation effects.

Projects

graph-tool

A comprehensive Python network library, including structural, dynamical and statistical algorithms, as well as visualization. Free and Open Source, released under the LGPLv3 license, fully documented, with high-performance algorithms written in C++, using template metaprogramming and OpenMP parallelism.  Available at: https://graph- tool.skewed.de

Netzschleuder

Online catalogue and repository of over 160K network datasets with the aim of aiding scientific research. The website is meant to be browsed both by humans and machines alike, and can also be accessed via a convenient JSON API, or via the graph-tool library. The network datasets themselves are available in several machine-readable formats, in particular gt, GraphML, GML and CSV.  Available at: https://networks.skewed.de

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