© Kay Herschelmann
Daniel Racek
Head of Department for Data Science and Software Development
About
I am a statistician and data scientist by training, interested in how we can better understand, analyse, and anticipate political violence, armed conflict, and war. My research connects statistical modelling and machine learning with substantive questions in conflict research and early warning, with a particular interest in developing methods for using unstructured data such as satellite imagery and text.
My broader aim is to develop methods that are both statistically sound as well as useful for real-world applications. In addition to conflict research, I work on general statistical and methodological problems in computational social science.
For my PhD dissertation, I received the KlarText Award for Science Communication and was selected as a finalist for the German Thesis Award (Deutscher Studienpreis). My work has also been covered by national and international media, including The Economist, Newsweek and the Tagesschau.
I am Head of the Department for Data Science and Software Development at the Center for Crisis Early Warning (CCEW), based at the University of the Bundeswehr Munich. Before joining the CCEW, I was a researcher at Ludwig-Maximilians-Universität (LMU) München, where I completed my PhD in Statistics under the supervision of Göran Kauermann, Xiaoxiang Zhu, and Paul Thurner through the Munich School for Data Science. I also hold an MSc. in Data Science and a BSc. in Economics from LMU, as well as a BSc. in Computer Science from the University of Derby.
I am always happy to chat about research, methods, or possible collaborations – just get in touch!
Latest
KlarText Award for Science Communication
Klaus Tschira Stiftung
Measuring war damage cost-effectively using radar satellites
Polytechnique Insights
Finalist, German Thesis Award (Deutscher Studienpreis)
Körber-Stiftung