I am a graduate student in computer science at Eberhard-Karls-University in Tübingen focusing on Artificial Intelligence. Before that, I studied computer science in a dual setup at the University of Applied Sciences in Stuttgart which involved frequent and extended industry research and development projects on topics regarding Manufacturing Execution Systems. The particular topics included work on Single Product Tracking, Improvement on Data Analysis as well as Key Performance Indicators. During that time I’ve also done research with Olaf Herden on NewSQL databases for modern Application Scenarios.
During my masters degree I attended internships such as the Extreme Blue internship at IBM, where I’ve researched the Connection between Internet of Things and Master Data Management. Also, I presented the obtained results at a conference in Cluj-Napoca, Romania. Currently I’m doing research on Deep Learning Optimizers with Philipp Hennig and Frank Schneider.
M.Sc. in Computer Science, 2020
B.Sc. in Computer Science, 2018
DHBW Stuttgart Campus Horb
A recent publication tried to parallelize K-FAC for multiple processes to speed up convergence. In this blog post I want to summarize the main contribution and give a little more insights.
Frequent and extended industry research & development projects during term breaks. This is approximately equivalent to 5 internships each with a duration of 3-4 months.
Some of them yielded whitepapers with the topics: