If you have not registered until the deadline, but are interested in attending: Please write us an email to berd-academy@stat.uni-muenchen.de including why you would like to attend. We still have a few spots open (for participation).
Mobile phone 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 peopleโs mobility and location. These data have been used, for example, in the COVID-19 years to assess the impact of non-pharmaceutical interventions on mobility patterns and firm location decisions as well as for traffic planning or academic research.
Under the umbrella of the BERD Academy, the workshop aims to bring together data scientists and researchers working on mobile phone data as well as related flow, geo-spatial and mobility data to address methodological as well as applied research questions from sociology, economics, or related fields. This includes the pre-processing of massive data, the restructuring of data into mobility data, or the detection of local clusters, to name just a few possible applications. The workshop provides an open forum for current research and new ideas on data analysis.
Nov 12, 2024
LMU Munich
Submission/Participation
Due to limited seat capacity and in order to keep the event interactive, applications for presentations will be given preference over requests for attendance only. We strongly encourage submissions from early-career researchers, including PhD students and practitioners. Contributions that are methodological or empirical in nature are welcome provided they use some kind of mobile phone data. While extended abstracts or early-stage drafts will be taken into consideration, complete papers will be given preference.
Timeline
Application/Submission deadline: September 30th
Confirmation/rejection: October 8th (at the latest)
Workshop: Tuesday, November 12, from midday to evening (more info to follow)
Scientific Committee
Gรถran 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.
Victor Tuekam is a doctoral student in Statistics at LMU Munich and the ifo Institute. His research interests are in generalized linear and mixed models, network data analysis, and urban economics.
Sebastian Wichert is the head of the LMU-ifo Economics & Business Data Center, the joint research data center of the ifo Institute and the LMU Munich. His research interests are in public economics, regional economics and household finance using and combining traditional statistical data with real-world data.
Contact:
berd-academy@stat.uni-muenchen.de
