About Me

Hi, I’m Johannes, a data scientist and machine learning engineer with a strong research background and a deep interest in uncovering patterns in complex data. What began during my computer science studies at the University of Augsburg soon evolved into a passion for modeling, analyzing, and interpreting data at scale.

During my PhD, I focused on machine learning, big data analytics, and explainable AI, developing scalable pipelines and tools that connect research and real-world application. Presenting my work at international conferences shaped how I see data — as both a scientific challenge and a creative process.

I’m passionate about bridging insights with impact — designing efficient, interpretable systems that make data-driven decisions tangible. Outside of work, I’m a cineast, photography enthusiast, and outdoor explorer — always drawn to stories, patterns, and perspectives, whether in film, data, or nature.

Curriculum Vitae

🎓 Academic Education

  • PhD in Information Science, University of Augsburg (2016 – 2024)
  • M.Sc. in Information Science, University of Augsburg (2013 – 2016)
  • B.Sc. in Information Science and Multimedia, University of Augsburg (2009 – 2013)

💼 Professional Experience

  • Data Analytics Consultant, Prodato Integration Technology GmbH (06/25 – 10/25)

    • Data integration & orchestration of pipelines in Azure Databricks Lakehouses
    • Design of ML pipelines and data-driven analyses for actionable insights

  • Postdoc & Research Associate, University of Augsburg (04/16 – 04/25)

    • Research on scalable ML pipelines and statistical analysis of complex datasets
    • Development of tools for User Role Detection & Preference Analytics
    • Led tutorials in DB and Big Data, coordinated academic management
    • Publications and presentations at international conferences

  • Research Assistant & Tutor, University of Augsburg (2011 – 2016)

    • Led exercises in Databases & Multimedia Foundations
    • Participated in research projects as a student assistant

🛠 Selected Projects

  • ANtIDOTE (2021 – 2023) – Efficient algorithms for large-scale information spread in social networks & media (DFG-funded)

    • Design & development of clustering & classification methods,
    • User Role Detection & Long-Term Evaluation

  • BigPREF (2016 – 2017) – Preference analytics in Big Data (Exasol AG, Nürnberg)

    • Design, development & analysis of innovative clustering methods

  • TSMP (2013 – 2015) – Tourism Service Matching Platform (Outdooractive AG, Immenstadt)

    • Backend design
    • development of showcase for preference-based offerings