{"id":10321,"date":"2025-01-13T10:51:02","date_gmt":"2025-01-13T09:51:02","guid":{"rendered":"https:\/\/www.uni.lu\/lcsb-en\/?post_type=events&p=10321"},"modified":"2025-01-28T13:01:58","modified_gmt":"2025-01-28T12:01:58","slug":"biomedical-data-plecca","status":"publish","type":"events","link":"https:\/\/www.uni.lu\/lcsb-en\/events\/biomedical-data-plecca\/","title":{"rendered":"Causal Analysis of Biomedical Data – Prof. Paola Lecca"},"content":{"rendered":"\n
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This is a remote-only event. <\/strong>Tune in via Webex here.<\/a><\/p>\n\n\n\n

\nIntegrating latent network geometry into mechanistic modelling of network dynamics<\/strong><\/strong><\/h2>\n\n\n\n

The concept of latent geometry of a network, that is the geometry of the latent metric space of the graph representing the network, has emerged from mathematicians\u2019 and theoretical physicists\u2019 classrooms to become an indispensable tool for determining the structural and dynamic properties of networks in many application areas, including contact networks, social networks, and, most notably, biological networks. In this talk, we will specifically explore latent geometry of some categories of biological networks to demonstrate how the geometry of the metric space of the graph, whether curve or flat, might affect the time evolution of the network.<\/p>\n\n\n

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\nAbout the speaker<\/h3>\n\n\n\n

Paola Lecca is Assistant Professor at the Faculty of Engineering of the Free University of Bolzano<\/a>, where she conducts research on graph theory, dynamical networks, control theory, and causal inference. As a member of the Faculty\u2019s Smart Data Factory laboratory,<\/a> she promotes technology transfer between academia and industry. She is also a Senior Professional Member of the Association for Computing Machinery<\/a>.<\/p>\n\n\n

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