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Data Science with Telecommunication Data

More details and registration available soon

Telecommunication data are ubiquitous today, as almost everyone carries a mobile device in their pocket. This generates huge data trails that provide almost unbiased information about people’s mobility and location. Such data have been used, for example, in the COVID-19 years to assess the impact of non-pharmaceutical interventions on mobility patterns.

The workshop will focus on the analysis of telecommunication data. This includes the pre-processing of massive data, the restructuring of data into mobility data such as flows, or the detection of local clusters, to name just few possible applications.

Under the umbrella of the BERD Academy, the workshop aims to bring together data scientists who work with or on telecommunication data and/or are interested in flow and mobility data to address applied research questions from sociology, economics or related fields. The workshop provides an open forum for current research and new ideas on data analysis.

:spiral_calendar_pad: Nov 12, 2024
:round_pushpin: LMU Munich

About the Instructor

Göran Kauermann has been a full professor of Statistics at LMU Munich since 2011 and heads the Chair of Statistics for Economics, Business, and Social Sciences there. Additionally, he is the chairman of the German Data Science Society (GDS). His research interests focus on semi- and nonparametric analysis, generalized linear and mixed models, and network data analysis.

Data Science for Social Good

Registration ended (Feb 15, 2023)

This 2-month full-time program joins forces of aspiring talents in the area of Data Science in small groups to work on projects with a positive societal impact.

The program is designed for two teams of 4-5 fellows, each working on a separate project for the social good. Both teams will be assisted by a Technical Mentor and a Project Manager. The participants receive a fellowship that covers living expenses for the time of the program from August 1st – September 30th.

The program is aimed at students, recent graduates or PhD students from diverse scientific, as well as geographical backgrounds. We therefore encourage applications from the fields of data science, computer science, statistics, but also in general the social and natural sciences.

If you are interested in joining the program or have students, friends or colleagues in mind that could be interested, check out the website and apply by February 15th: https://sites.google.com/view/dssgx-munich-2023/startseite

Please also share this call in your network, in classes you teach or approach people directly.

In case of any concerns please feel free to reach out via dssg2023@stat.uni-muenchen.de

About the Host and the organizing Institution

This Event is hosted by the Chair of Frauke Kreuter, who is a professor of Statistics and Data Science in the Social and Behavioral Sciences at LMU Munich. In her research, she focuses on statistical methods related to labor market and occupational research, as well as data science. In addition to her academic work, she is the founder or co-founder of several programs that address evolving data environments and data-driven research. The Munich Center for Machine Learning (MCML) is one of six national AI Competence Centers and brings together the leading ML researchers from LMU, TUM and associated institutions.