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  • Tensor Decomposition Techniques for analysing time-varying networks

    Tue, Oct 11, 2016 @ 11:00 AM - 12:00 PM

    Information Sciences Institute

    Conferences, Lectures, & Seminars

    Speaker: Anna Sapienza, PhD in Applied Mathematics at the Polytechnic Univ. of Turin, working in the Data Science Lab at ISI Foundation, Turin, Italy

    Series: Recruitng Seminar

    Abstract: The increasing availability of high-dimensional data calls for new methods to extract meaningful information, such as groups of data correlations (i.e. communities, clusters) or unusual and unexpected data records (i.e. anomalies, outliers). Time-varying networks are particularly suitable objects to summarize a large amount of data into interpretable representations and are used to describe a great variety of complex systems. A fundamental challenge is to define models and tools that are able to capture and disentangle the structural and temporal properties from the time-varying networks and reproduce the observed features on dynamical processes occurring over the network, such as information diffusion, event cascades or disease spreading. Thus, the purpose of my Ph.D work is twofold: to extract the structural and temporal properties of time-varying networks to face problems as pattern detection and missing data recovery, and to analyze the interplay between these characteristics and dynamical processes.

    Biography: Anna Sapienza is currently a Ph.D candidate at the Polytechnic University of Turin, she is completing the third year of her Ph.D studies. Her work was developed in the Data Science group at the I.S.I. Foundation of Turin under the supervision of Dr. Ciro Cattuto and Dr. Laetitia Gauvin. Her research interests stay at the intersection between computational social science, machine learning, and network analysis. Recently her work focused on the development of mathematical frameworks and tools for tensor factorization techniques and their applications for studying high-dimensional data.

    Host: Emilio Ferrara and Kristina Lerman

    Webcast: http://webcastermshd.isi.edu/Mediasite/Play/e7f614b9cffc415db4015dd86999db5f1d

    Location: Information Science Institute (ISI) - 1135 - 11th fl Large CR

    WebCast Link: http://webcastermshd.isi.edu/Mediasite/Play/e7f614b9cffc415db4015dd86999db5f1d

    Audiences: Everyone Is Invited

    Contact: Alma Nava / Information Sciences Institute

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