I am a research scientist/postdoc at the chair of information theory and machine learning at Technische Universität Dresden where I work at the intersection of information theory and ML. I did my Dr.-Ing. (PhD) at the Technische Universität Berlin advised by Gerhard Wunder. My thesis was about deterministic models for capacity approximations in interference networks and physical layer security. I received the M.Sc. degree in electrical engineering from the Technische Universität Berlin in 2012 and the B.Sc. degree in electrical engineering from the Hochschule Furtwangen University in 2010.

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Research

I am generally interested in the topics of Information theory, Security, Fairness, Machine learning, and Statistics. My research spans the following topics:

• Information theory: Investigating the theoretical limits of data compression and transmission
• High-dimensional statistics: Exploring estimation methods and theoretical properties in high-dimensional spaces, particularly for applications in AI
• AI applications in wireless: Diffusion models, Interplay between classical codes and AI coding schemes
• Estimation methods for mutual information

Recent News

• May, 2024. My collegue Muah Kim gave a tutorial about Diffusion models at ICMLCN 2024 based on our work
• January, 2023. Our recent paper on “Learning End-to-End Channel Coding with Diffusion Models” co-authored with Muah Kim and Rafael Schaefer got accepted
• January, 2023. I have started working at TU Dresden
• December, 2022. Our recent paper on “Concatenated Classic and Neural (CCN) Codes: ConcatenatedAE” co-authored with Onur Günlü and Rafael Schaefer got accepted
• Februar, 2022. I have started working at Uni Siegen
• Oktober, 2019. I have started working at FU Berlin

Contact

Email: rick.fritschek at tu-dresden.de, rickfritschek at gmail.com