# Christoph Molnar

> Christoph Molnar is a Munich-based statistician-turned-ML-author who turned a side project into the field's most-cited book on interpretable machine learning. Author of six books including the canonical 'Interpretable Machine Learning' (3rd ed., 2025), he runs the Mindful Modeler newsletter and consults on making black-box models explainable. With 16,000+ Google Scholar citations and a PhD from LMU Munich, he sits at the precise intersection where statistical rigor meets machine learning pragmatism.

- **Role:** Self-Employed ML Author and Consultant
- **Organizations:** LMU Munich (alumnus), SCQM Foundation (former), Centralway AG (former), BIPS GmbH (former), Johner Institute GmbH (former)
- **Nationality:** German
- **Education:** PhD in Interpretable Machine Learning, Ludwig-Maximilians-Universität München (LMU), MSc in Statistics, Ludwig-Maximilians-Universität München (LMU), BSc in Statistics, Ludwig-Maximilians-Universität München (LMU)
- **Known for:** 16,000+ Google Scholar citations for 'Interpretable Machine Learning', Author of 6 books on ML interpretability, conformal prediction, remote sensing, and modeling, Created the iml R package implementing interpretation methods

## Career timeline

- **2010-2014** — Various student and side roles during BSc/MSc studies at LMU Munich
- **2012** — First Kaggle competition - placed 463rd out of 699, only knowing linear models at the time
- **2014-2015** — Data Scientist at Centralway AG (startup)
- **2016-2017** — Statistician at SCQM Foundation, clinical research data work
- **2017** — Discovered the LIME paper, sparking deep interest in interpretability; started 'Interpretable Machine Learning' as a side project
- **2017-2021** — PhD Candidate at LMU Munich, focusing on interpretable machine learning
- **2020** — Keynote speaker at ECML-PKDD 2020 and Johner Institutstag 2020
- **2021** — Researcher at BIPS GmbH (Jun-Sep); AI Consultant at Johner Institute GmbH (Oct-Dec)
- **2022** — Completed PhD from LMU Munich; quit postdoc after ~3 months; went self-employed full-time as ML author
- **2023** — Published 'Modeling Mindsets' and 'Introduction to Conformal Prediction With Python'; Mindful Modeler newsletter grew to 16k+ subscribers
- **2025** — Released 3rd edition of 'Interpretable Machine Learning' (ISBN 978-3-911578-03-5)

## Achievements

- 16,000+ Google Scholar citations for 'Interpretable Machine Learning'
- Author of 6 books on ML interpretability, conformal prediction, remote sensing, and modeling
- Created the iml R package implementing interpretation methods
- Keynote speaker at ECML-PKDD 2020
- Interpretable Machine Learning book used in universities worldwide
- 16,000+ newsletter subscribers (Mindful Modeler on Substack)
- 5,000+ GitHub stars on interpretable-ml-book repository
- Featured in Süddeutsche Zeitung and major ML podcasts

## Latest updates

- **2025-01** — Released 3rd edition of 'Interpretable Machine Learning: A Guide for Making Black Box Models Explainable' (ISBN 978-3-911578-03-5), with reorganized introduction, new Palmer penguin dataset replacing cancer dataset, and practical tips/warning boxes
- **2024-01** — Actively developing 'Machine Learning for Remote Sensing' book at book.ml4rs.com
- **2023-10** — Became full-time writer/author; Mindful Modeler newsletter reached 16k+ subscribers
- **2023-01** — Published 'Introduction to Conformal Prediction With Python' and 'Modeling Mindsets'

## Links

- Website: https://christophmolnar.com/
- LinkedIn: https://www.linkedin.com/in/christoph-molnar/
- Twitter/X: https://twitter.com/christophmolnar
- GitHub: https://github.com/christophM

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Profile page: https://yespress.io/christoph-molnar
Published by YesPress — https://yespress.io
Last updated: 2026-04-22