AIMS-TUC Workshop Applied Mathematics

at TU Chemnitz, 24.09.2018 - 29.09.2018

organized by Mouhamed Moustapha Fall, Franck Kalala Mutombo and Aissa Wade (AIMS Senegal) and Alois Pichler, Vladimir Shikhman and Peter Stollmann (TU Chemnitz)

Extended lectures by Franck Kalala Mutombo, Alois Pichler, Vladimir Shikhman and Peter Stollmann; moreover participants got the possibility to present their own research.

Travel grants for young researchers from african countries had been available due to the generous support by the DAAD.

The following courses had taken place:

'An introduction to networks analytics and applications' by F.K. Mutombo, AIMS Senegal
Abstract: This course will provide a broad range of approaches and techniques drawn from social network analysis, graph theory, and network science for analyzing real-world network data. During the course, theoretical material will be presented together with data and code using NetworkX in Python in the Jupyter Notebook environment (or spyder). Specific topics include, but are not limited to, the following:

The basic conceptual and mathematical formulation of networks

Basic metrics of networks (e.g. paths, components, degree distributions, etc.)

Centrality measures, General properties of real-world networks, Models of networks, Dynamics of, and on, networks, Community detection

Social Network Analysis

'Stochastic optimization' by A. Pichler, TU Chemnitz
Abstract: The lecture discusses optimization problems under uncertainty first. It turns out that a main bottleneck is the probability measure. We address simplifications of the probability measure, so that the stochastic programs get simpler and computationally tractable. An important tool is the Wasserstein distance. This concept of distance allows relations to the other lectures in program.

'Ranking and Clustering in Networks' by V. Shikhman, TU Chemnitz
Abstract:The focus will be on ranking and clustering in networks by using tools from numerical linear algebra and optimization theory. Relevant applications from Big Data Analytics, e.g. community detection in social networks, brand loyalty, and surfing on the Web will be elaborated in detail.

'Directed graphs -- operator theoretic basics for networks' by P. Stollmann, TU Chemnitz
Abstract: Directed graphs are an important mathematical tool for applications in a wide variety of fields. We will focus on certain basic mathematical features, in particular: invariant vectors and the convergence to equilibrium.

The workshop was supported by the

-- Gefördert vom DAAD aus Mitteln des Bundesministeriums für Bildung und Forschung (BMBF) --