Tobias Fritz M.Sc.

Tobias Fritz M.Sc.

 

Research Area:

Tobias' current research area is in the domain of graph neural networks. Here, he is especially interested in applying these for the task of fake news detection in social media networks as well as computer network analysis. Further, he is interested in Large Language models and their application in various domains.

Before starting his doctorate, he worked for one year as a software developer. He received his master's degree in mathematics from the Technical University of Munich and his bachelor's degree in mathematics with a minor in computer science from the Ludwig-Maximilians-Universität. During his studies he worked in research departments at Infineon Technologies AG and Allianz Global Investors GmbH for about 3 years.

 

Publications:

L. Servadei, E. Zennaro, T. Fritz, K. Devarajegowda, W. Ecker, R. Wille. November 2019.  Using Machine Learning for Predicting Area and Firmware Metrics of Hardware Designs from Abstract Specifications. In Microprocessors and Microsystems,  https://doi.org/10.1016/j.micpro.2019.102853

 

Seminar/Bachelor/Master Thesis Topics:

Large Language Models for Fake News Detection: Large Language Models are at the heart of tools like ChatGPT, which have shown extrodinary performance in tasks thought to be only performed by humans before. In this thesis, different large language models will be compared with respect to architecture and performance and a small application of these models to the task of fake news detection will be implemented.

Large Language Models for Penetration Testing: Large Language Models can be used for code generation and code completion, for example in Microsoft Copilot. In this thesis, different large language models will be compared with respect to architecture and performance. Furthermore, the ability of these models to find security weaknesses in given pieces of code will be evaluated.

 

Please approach me if you want to propose your own idea within my area of interest.