Christopher is a Research Assistant in the Intelligent Interactive Systems Group (IISY) supervised by Prof. Kristian Hildebrand. He graduated with a Master's degree in Media Informatics at the Beuth University of Applied Sciences Berlin in October 2018.
In his Master's Thesis Christopher developed a system, which allows the comparison of different sampling approaches in an Active Learning scenario.
The task was to enable the user to compare and develop Reinforcement Learning approaches to eventually reduce costs of training machine learning models in the field of NER.With his employment at the IISY group his focus switched to computer vision related tasks, which are also linked to NLP.
Currently he researches and develops end-to-end neural sign language translation systems.
Christopher also works in the BMBF founded research project BewARe.
In BewARe he is responsible for integrating novel machine learning approaches to support senior citizens in health issues.
Research Interests
- Neural Machine Translation
- Multi-modal Learning
- Deep Learning / Computer Vision
Talks
- "Reducing Machine Learning costs with Active Learning" at [Data&Drinks](https://www.meetup.com/meetupai-Berlin/events/czmfhqyxpbkb/) - 07.11.2018
Projects
Contact
E-Mail: christopher.kuemmel(at)bht-berlin.de
https://www.linkedin.com/in/christopherkuemmel/
