About Me

I am a second year Ph.D. student at Martin Spindlers Chair of Statistics with Applications in Business Administration at University of Hamburg. My research focusses on applying machine learning to causal effect estimation to understand relationships in the data that go beyond correlations. I work on software implementations and applications of causal machine learning frameworks. I am contributor of the python package DoubleML. I have worked as a data scientist at Economic AI before.

Research Interests

• Causal Machine Learning: heterogeneous treatment effect estimation, double machine learning, causal reinforcement learning, policy learning
• Deep Learning and Reinforcement Learning for causal inference
• Applications to healthcare, economics and engineering

News

• [Jan. 2024] Our work about hyperparameter tuning in the double machine learning framework has been accepted to the 2024 Clear Conference.
• [Oct. 2023] I am honored to present our application of causal policy learning to semiconductor manufacturing at the 2023 Causal Data Science Meeting.
• [Aug. 2023] I am visiting Prof. Biwei Huang at Halıcıoğlu Data Science Institute, University of California, San Diego for the next five months.
• [Jun. 2023] Our paper about causal policy learning in a manufacturing setting got accepted at the Causality workshop of KDD 2023.

Publications

Contact

If you are interested in collaborating, feel free to reach out.

Address: Moorweidenstraße 18, 20148 Hamburg, Germany
Office Location: Room 0025
Email: oliver . schacht (at) uni-hamburg.de
Phone: +49 40 42838-1517