Currently researching data science and linked data methods for the digitalization and FAIR-ification[1] of various laboratory processes. This research aims to facilitate the use of machine learning methods in the analysis of the data generated by these processes.

Additionally, it will make the data more easily accessible and usable by researchers from around the globe.

Previous experiences include a variety of machine learning projects in areas such as remote sensing, finance, recommender systems, and more.

[1] https://www.go-fair.org/fair-principles/

Publications

Fabian Schenkel, Benjamin Wohnhas, Wolfgang Gross, Simon Schreiner, Ilia Bagov, and Wolfgang Middelmann "Ship detection and classification with terrestrial hyperspectral data based on convolutional neural networks", Proc. SPIE 11155, Image and Signal Processing for Remote Sensing XXV, 111550K (7 October 2019); https://doi.org/10.1117/12.2533090