University of Hamburg – An Introduction to Causal Machine Learning with doubleML

June 14th, 11.00 am – 12.00 pm

While Machine Learning methods have been developed for prediction tasks, many interesting problems in industry and research are causal questions. Examples are pricing, personalized marketing, production optimization, resource allocation and many more. Using Machine Learning for Causal Inference has been an active field in the recent years. In this talk the double ML approach is introduced. Moreover, several case studies will be presented to showcase the applications of causal machine learning.



Prof. Dr. Martin Spindler, Professor of University of Hamburg

picture of Martin Spindler-sqaure

Martin Spindler is Professor of Data Science, Statistics & Econometrics, at the University of Hamburg. In his research he works on the theory and practical applications of Machine Learning and AI, in particluar Causal Machine Leraning. He studied at the University of Regensburg and University of Munich, obtained his PhD from the University of Munich and is a visiting scholar at MIT on a regular basis. The applications, he has worked on, comprise amongst others Dynamic Pricing, Financial Forecasting and Planning, advanced A/B Testing and targeted Marketing.