Hey, I am Felix.

I am an entrepreneurial thinking physicist, currently pursuing a PhD and a part-time MBA. At the moment, I am working on my final PhD thesis. Afterwards, this website will be properly updated.

Just reach out to me via e-mail.


  • Artificial Intelligence, Machine Learning and Python Programming
  • Ambitious Business Ideas and Startups in Technology
  • Hyperspectral Remote Sensing
  • 10k Runs and Multi-Day Hikes


  • PhD in AI and Remote Sensing, (2020)

    Karlsruhe Institute of Technology

  • MBA, (2020)

    Collège des Ingénieurs

  • M.Sc. in Particle Physics, 2017

    Karlsruhe Institute of Technology

  • B.Sc. in Physics, 2014

    Karlsruhe Institute of Technology

Recent Talks

Talks, workshops and media.

Radio interview about 'Künstliche Intelligenz - Trinkwassersuche mit Satelliten und KI'

Radio interview by Anna Caroline Hein about the work of Felix M. Riese and Sina Keller in the field of artificial intelligence and …

Video about 'Künstliche Intelligenz in der Umweltforschung'

Video about the Trust project funded by BMBF and about my PhD in artificial intelligence, remote sensing and environmental science.

Podcast episode about 'Fernerkundung mit multispektralen Satellitenbildern'

We were part of the German TechTiefen podcast with Nico Kreiling about multispectral satellite computer vision. We explain our attempt …


Journal articles, conference papers etc.

Supervised and Semi-Supervised Self-Organizing Maps for Regression and Classification Focusing on Hyperspectral Data

Machine learning approaches are valuable methods in hyperspectral remote sensing, especially for the classification of land cover or …

Soil Texture Classification with 1D Convolutional Neural Networks based on Hyperspectral Data

Soil texture is important for many environmental processes. In this paper, we study the classification of soil texture based on …

SUSI: Supervised Self-Organizing Maps for Regression and Classification in Python

In many research fields, the sizes of the existing datasets vary widely. Hence, there is a need for machine learning techniques which …

Examples for CNN training and classification on Sentinel-2 data

Overview about state-of-the-art land-use classification from satellite data with CNNs based on an open dataset.

Developing a machine learning framework for estimating soil moisture with VNIR hyperspectral data

In this paper, we investigate the potential of estimating the soil-moisture content based on VNIR hyperspectral data combined with IR …

Fusion of hyperspectral and ground penetrating radar data to estimate soil moisture

In this contribution, we investigate the potential of hyperspectral data combined with either simulated ground penetrating radar (GPR) …

Introducing a Framework of Self-Organizing Maps for Regression of Soil Moisture with Hyperspectral Data

In this paper, we introduce a framework to solve regression problems based on high-dimensional and small datasets. This framework …

Modeling Subsurface Soil Moisture Based on Hyperspectral Data: First Results of a Multilateral Field Campaign

Soil moisture dynamics and its spatial distribution represent important data of a landscape. Until today, a precise and spatially …