I am a Ph.D. student in the IMPRS-IS supervised by Bernhard Schölkopf. I research the potential of defining machine learning models via quantum computers. Check out our recent work on The Inductive Bias of Quantum Kernels. 

Furthermore I work on kernel based hypothesis test and how they can be made as data-efficient as possible.

You can find all my publications on my Google Scholar profile.

I plan to obtain my PhD in 2022.

Besides Research, I am also a member of the Tübingen City Council.

NEWS:

• Febraury '22: I was awarded a "best 10% of reviewers"-award from AISTATS 2022. Happy to contribute to the scientific community in this way.
• January '22: Our Paper A Witness Two-Sample Test was accepted at AISTATS 2022. The arXiv contains the camera-ready version.
• September '21: Our Paper The Inductive Bias of Quantum Kernels is accepted at NeurIPS2021.
• June '21 to September '21: I am pausing my PhD and will be on an internship at Amazon.
• June '21: New work on the possibilties and limitations of Machine Learning with Quantum Computers. Check out The Inductive Bias of Quantum Kernels
• February '21: Check out our new work: An Optimal Witness Function for Two-Sample Testing
• Winter '21: I will do an industrial internship this summer :)
• September '20: NeurIPS accepts our paper Learning Kernel Tests Without Data Splitting. I will present a poster at this year's virtual conference. We will update the paper soon.
• May '20: Our Work on Kernels for conditional moment restrictions is accepted to UAI20
• May '20: Quantum publishes our work on optimization of variational algorithms. This is the result of last years LANL summer school.
• From June to August 2019 I am a visitor at LANL for the quantum computing summer school.
• December '19: Physical Review Research publishes our paper Quantum Mean Embedding of Probability Distributions 
• August '18: New Journal of Physics publishes the work resulting from my Masters on Quantum Causality

Kernel Methods Quantum Machine Learning Hypothesis Testing