Jonas Seng

TU Darmstadt, Computer Science

Contact

TU Darmstadt
Machine Learning Group
Computer Science Department
Hochschulstr. 1
64289 Darmstadt

data_science@nhr4ces.de
LinkedInTwitter: @jonas_seng

Biography

is a PhD candidate at TU Darmstadt and joined NHR4CES in the CSG Data Science & Machine Learning group in 2021. He holds a Bachelor’s degree in Computer Science from DHBW Mannheim and a Master’s degree from TU Darmstadt. His research focuses on AutoML, including interactive hyperparameter optimization, neural architecture search, and federated AutoML. He is also interested in causal modeling to improve the robustness of machine learning systems.

Thematic Advice

More and more data is being produced every day in economic and research-driven environments. Thus Machine Learning (ML) techniques are on the rise in order to analyze such data and to build predictive models, recognizing patterns that could not be discovered by humans. AutoML is the next logical step in this development, enabling even non-experts to use sophisticated ML-tools to deal with their data at hand.

Jonas can offer experience in building new Machine Learning solutions which fit the needs of domain-experts and tries to establish AutoML-methods to allow domain-experts to use ML-tools without the need of a detailed understanding of ML.

Professional Competence

Jonas‘ focus lies in AutoML, an upcoming research field aiming to provide end-to-end ML-solutions that automatically solve ML-problems of domain-experts. His research interests within AutoML lie in Hyperparameter Optimization, Neural Architecture Search and Explainability of such methods.
In the context of HPC, his goal is to build scalable and explainable AutoML-methods that can be used to e.g. enable parallel and federated Hyperparameter Optimization allowing insights into the optimization process, thus making it interpretable.