Andreas Grafberger
Software and ML Engineer
Biography
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.
Interests
- Software Engineering
- Machine Learning
- Cloud Computing
- Web Development
Education
-
M.Sc. Informatics (with high distinction), 2021
Technical University of Munich
-
B.Sc. Informatics and Multimedia, 2018
University of Augsburg
Publications
(2021).
FedLess: Secure and Scalable Federated Learning Using Serverless Computing.
IEEE BigData 2021.
(2021).
ProteomicsDB: toward a FAIR open-source resource for life-science research.
Nucleic Acids Research.
(2018).
Automating large-scale data quality verification.
VLDB.
