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Machine learning researcher focused on probabilistic and open-source methods for efficient model adaptation. Experienced in building reliable ML pipelines that bridge research and real-world applications.

Experience

  • 2024 – present

    Munich

    Senior AI Researcher
    appliedAI Institute for Europe — TransferLab
    • Leading development of production ML systems — fine-tuning vision models (SAM with LoRA) for environmental monitoring, deployed as a QGIS plugin for public-sector use.
    • Consulting on Large Industry Models (LIMs) for the German automotive sector, evaluating specialized vs. general-purpose AI strategies for industrial applications.
    • Developing and maintaining open-source software for accessible AI/ML tools, including the sbi package for simulation-based inference.
    • Implementing MLOps pipelines with experiment tracking and model versioning for reproducible research-to-production workflows.
    • Designing and delivering workshops on recent AI/ML topics for academics and industry professionals.
  • 2021 – 2023

    Tübingen

    Doctoral Researcher
    University of Tübingen — Machine Learning in Science
    Supervisor — Prof. Jakob Macke
    • Simulation-based inference for models of decision-making.
    • Accessible software tools for simulation-based inference.
  • 2018 – 2020

    Munich

    Doctoral Researcher
    Technical University of Munich — Computational Neuroengineering
    Supervisor — Prof. Jakob Macke
    • Simulation-based inference for computational connectomics.
  • 2015

    Berlin

    Research Assistant
    Technical University of Berlin — Brain-Computer Interfaces
    Supervisor — Prof. Benjamin Blankertz
    • Study design and analysis of EEG brain-computer interfaces.
  • 2013 – 2014

    Vancouver, CA · Bogotá, CO

    Research Intern
    Various Institutions
    • Research across cognitive neuroscience, biomedical engineering, and fMRI data analysis.

Education

  • 2023
    Ph.D. in Computer Science
    University of Tübingen
    Probabilistic Machine Learning for Neuroscience. Advisor — Prof. Jakob Macke.
  • 2018
    M.Sc. in Computational Neuroscience
    Technical University Berlin
    With Distinction.
  • 2015
    B.Sc. in Cognitive Science
    University of Osnabrück
    With Distinction.

Community & outreach

  • since 2021
    Maintainer — sbi
    Python package for simulation-based inference
  • since 2022
    Reviewer
    NeurIPS, AISTATS, ICML, ICLR, JOSS, PLOS
    Best Reviewer Award, ICML 2024 & 2025.
  • since 2021
    Lecturer
    KI macht Schule — teaching AI to German high-school students
  • 2023
    Mentor
    Neuromatch Academy (Computational Neuroscience Track) · Google Summer of Code
  • since 2022
    Co-organizer
    SBI Workshop 2022 · SBI Hackathon 2024 & 2025