Andreas Grafberger

Andreas Grafberger

Software and ML Engineer


I recently completed my master’s degree with high distinction from the Technical University of Munich. During my studies, I specialized in machine learning and software engineering. I especially enjoy working at the intersection of both fields.

I wrote my master’s thesis on Secure and Scalable Federated Learning using Serverless Computing, which I was honored to present as a paper at IEEE BigData 2021.

In the past, I have interned at both Amazon Search and Amazon Core ML, and I worked as a Research Assistant at the Technological University of Munich and the University of Augsburg.

  • Software Engineering
  • Machine Learning
  • Cloud Computing
  • Web Development
  • M.Sc. Informatics (with high distinction), 2021

    Technical University of Munich

  • B.Sc. Informatics and Multimedia, 2018

    University of Augsburg


(2021). FedLess: Secure and Scalable Federated Learning Using Serverless Computing. IEEE BigData 2021.

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(2021). ProteomicsDB: toward a FAIR open-source resource for life-science research. Nucleic Acids Research.

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(2018). Automating large-scale data quality verification. VLDB.

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