About Me

Welcome to my page. I am a former researcher with the Computer Vision Group, FSU Jena, Germany and with the Climate Informatics Group, German Aerospace Center (DLR), Institute of Data Science, Jena, Germany. Now I am working as a freelance machine learning engineer, data scientist and software developer.

You can also find me on LinkedIn and Google Scholar, or you can contact me via email.

Dr. Christoph Käding

Short CV

2022 – today

Freelance machine learning engineer, data scientist and software developer


Graduation as doctor rerum naturalium, doctoral thesis: ”Human-in-the-Loop: Lifelong Learning for Shallow and Deep Models“

2019 – 2022

Research associate and postdoc in the Climate Informatics Group of the German Aerospace Center (DLR), Institute of Data Science, Jena, Germany – machine learning for causal inference in climate data, assessment and systematic study of algorithms for distinguishing cause and effect from purely observational data

2014 – 2018

Research associate in the Computer Vision Group of the Friedrich Schiller University Jena, Germany – development of lifelong learning concepts (i.e., incremental learning, active learning, and novelty detection), analysis of camera trap images for wildlife surveillance research


Master of Science in Computer Science, master thesis: ”Active Learning for Object Detection and Multiclass-Classification“

2012 – 2014

Studies at Friedrich Schiller University Jena, Germany – focus on computer vision and machine learning

Please contact me for a complete CV and further details.

Skills and Competencies


  • 14 years of programming experience (10 years Matlab, 9 years Python incl. common libraries like NumPy, Pandas, Keras / Tensorflow, Matplotlib, scikit-learn, etc.)
  • 12 years of basic as well as application-driven research in international and interdisciplinary environments (DFKI, FSU Jena, DLR)
  • 8 years of practical experience in concrete implementation and technical support / management of projects with various scientific and industrial partners


  • German (mother tongue)
  • English (fluent spoken and written)

Knowledge and Technologies

  • Machine learning, data science, software development
  • Computer vision, classification, object detection, segmentation, regression, novelty / anomaly detection, active learning, incremental learning, lifelong learning, transfer learning and domain adaptation, causal discovery / causal inference, deep learning and traditional ”shallow” learning (e.g., GP, SVM, OLS, kernel methods, etc.)
  • Data and feature engineering / ETL, data analytics and visualization / EDA, interpretability of models / data
  • DevOps, MLOps, CI/CD, building ML pipelines, version management (e.g., Git)
  • Computing cluster manager and distributed computing (e.g., Slurm), cloud infrastructures (e.g., AWS), containers and virtualization (e.g., Docker), web APIs (e.g., REST)
  • Images, volumes / image stacks, time series, tabular / structured data

This is a non-exhaustive list. Please contact me for more details.

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