Dennis Fast joined the DATEXIS team as a Research Assistant in January 2022 with a focus on Transformer-based Language Models. His current research area is the practical application of Natural Language Processing (NLP) in the medical domain.
Currently, he is working on the project COMFORT, funded by the European Union. The main objective of the project is to create AI models to support medical professionals in improving the care of people with prostate or kidney cancer. The main focus of his work is to develop trustworthy multimodal AI models by utilizing different types of health data, including image data, medical health records, and biomarkers.
Dennis first came into contact with data processing during his education as a physical-technical assistant, where he acquired the foundations of statistical data analysis and an awareness of the importance of the reproducibility and interpretability of results during a large number of experiments in various areas of physics.
He then studied Applied Maths with a specialisation in Physical Simulations at BHT (formerly Beuth University of Applied Sciences) in Berlin and in March 2018 he graduated from there with an MSc in Computational Engineering with a specialisation in Acoustic Simulations. During this time, he worked in several research teams at the university to immediately translate the acquired knowledge into real-world applications on the one hand and to deepen the fundamental knowledge on the other hand.
The growing awareness of the limitations of conventional analysis and simulation methods, the advanced maturity of Machine Learning algorithms and his interest in neural networks have finally inspired him to pursue a second Master's in Data Science at BHT in October 2021. There he found a passion for the Deep Learning algorithms in general and for the real-world applications of Language Models in particular. After completing his second Master's degree, he increasingly focused on the application of Language Models in the medical domain.
In his free time, Dennis mostly enjoys spending time with his family, hiking or cycling. He also enjoys listening to inspiring podcasts with successful scientists and reading positive science fiction books about the bright future of humanity to which he would like to contribute with his knowledge and experience.
Research Interests:
- Deep Learning
- Applications of NLP in Medical Domain
- Multimodal AI Models
Publications:
- Torsten Kohrs, Karl-Richard Kirchner, Dennis Fast, Alberto Vallespin, Joan Sapena, Ainara Guiral Garcia, Otto Martner: Sound propagation and distribution around typical train carbody structures. Euronoise 2018
- Svenja Hainz, Dennis Fast, Siv Leth, Elodie Vannier, Rüdiger Garburg: Noise Assessment of Railway Innovations, Hands on Sustainable Mobility 2019
- Karl-Richard Kirchner, Dennis Fast, Torsten Kohrs, Haike Brick: Airborne sound source characterization for railway noise predictions - based on vibration measurements and numerical simulations, Internoise 2019
- Torsten Kohrs, Karl-Richard Kirchner, Dennis Fast, Haike Brick, Ainara Guiral Garcia: Industrial engineering framework for railway interior noise predictions, IWRN13 2019
Contact :
E-Mail: dfast (@) bht-berlin.de
