Photo: Pia Pöhlmann

This is the interview podcast peaking behind the scenes of data analysis of business, academia, and politics.

Dr. Annika B. Bergbauer

Tech economist

Annika Bergbauer holds a Ph.D. in economics by the LMU Munich and is a data expert. She works as IT and mangement consultant in the Munich area.

As data scientist and project manager she develops solutions for her clients, develops concepts, and trainings. Annika promotes diversity & inclusion in the consulting industry.

The podcast Datenaffaire was nominated for the For… Net Media Award 2022 which honors dedication to communicating digitalisation for the common welfare.

She regularly gives talks at universites, publishes articles, and moderates discussions.
Annika has administred an expert network of the European Commission, „European Expert Network on Economics of Education (EENEE)“.

Her book „Conditions and consequences of education – microeconometric analyses“ was published in the ifo Beiträge zur Wirtschaftsforschung, in 2019. At the ifo Institute in Munich, Annika Bergbauer researched the economics of education with Prof. Ludger Wößmann and Standford professor Rick Hanushek. Their research is forthcoming in the Journal of Human Resources (Handelsblatt ranked A journal in economics) and already published as NBER Working Paper, and at vox.eu and oekonomenstimme.de. Her single-authored paper was published at Education Economics. Annika Bergbauer started her academic career at the University of Stellenbosch, in South Africa supervised by Prof. Servaas van der Berg. Her South African research is published as Stellenbosch Economic Working Papers and work with the psychologist Dr. Surette van Staden in the International Journal of Instruction and in the South African Journal of Childhood Education.

Annika Bergbauer has presented her research at reknown conferences around the world.
She graduated from the University of Göttingen with a Bachelor and a Master degree in economics with semesters abroad in Delhi and Paris.

Her academic career was supported by the Smith Richardson Foundation, several stipends by the DAAD, and the AKB Foundation.

Episode 67 – Machine Learning in der Parasitologie  Datenaffaire

Photo: Sascha Mannel. Warum analysiert man die Zellen eines Wurms? Und wie kann Machine Learning dabei helfen? Oliver Puckelwaldt, promoviert an der Justus-Liebig-Universität Gießen am Institut für Parasitologie. Er erforscht das Leberegel, das für Tiere und Menschen in armen Regionen gefährlich ist. Auf Basis seiner Grundlagenforschung kann dann ein Medikament entwickelt werden.  Links zu Episode […]
  1. Episode 67 – Machine Learning in der Parasitologie 
  2. Ep. 66 – KI oder Mensch – Wer entwirft das bessere Lauftraining
  3. Episode 65 – Diversity braucht Daten
  4. Sommerpause