Clemens-Alexander Brust

Clemens-Alexander Brust

🧪 research in ML methods and applications ǀ 🏢 team lead Secure Software Engineering at DLR Data Science ǀ 🎓 FSU Jena

Hi! Thanks for visiting my page. I am a group lead at the DLR Institute of Data Science in Jena, responsible for our Secure Software Engineering Group. We apply and advance machine learning methods to provide software developers with tools, methods and processes that support them in developing secure software.

Previously, I completed my PhD with the Computer Vision Group at Friedrich-Schiller-Universität Jena on the integration of semantic knowledge and machine learning. Semantic knowledge can help fill the gap and interpret new types of data, for example imprecise labels.

If you are interested, check out my CV and publications.

Selected publications

Towards Enabling Level 3A AI in Avionic Platforms
AvioSE 2023 | pdf
Wanja Zaeske and Clemens-Alexander Brust and Andreas Lund and Umut Durak

Pre-trained models are not enough: active and lifelong learning is important for long-term visual monitoring of mammals in biodiversity research
Mamm. Biol. 2022
Paul Bodesheim and Jan Blunk and Matthias Körschens and Clemens-Alexander Brust and Christoph Käding and Joachim Denzler

Generalizability of Code Clone Detection on CodeBERT
ASE 2022 | pdf
Tim Sonnekalb and Bernd Gruner and Clemens-Alexander Brust and Patrick Mäder

Making Every Label Count: Handling Semantic Imprecision by Integrating Domain Knowledge
ICPR 2020 | pdf
Clemens-Alexander Brust and Björn Barz and Joachim Denzler

Integrating Domain Knowledge: Using Hierarchies to Improve Deep Classifiers
ACPR 2019 | pdf
Clemens-Alexander Brust and Joachim Denzler

Towards Automated Visual Monitoring of Individual Gorillas in the Wild
ICCV-WS 2017 | pdf
Clemens-Alexander Brust and Tilo Burghardt and Milou Groenenberg and Christoph Käding and Hjalmar Kühl and Marie L. Manguette and Joachim Denzler

See more of my publications here!

Projects

  • ROMEO: Exploring Juliet through the Lens of Assembly Language. GitLab
  • CHILLAX: Concept hierarchies for imprecise label learning and annotation extrapolation. GitHub
  • CHIA: Concept hierarchies for incremental and active learning. GitHub