About the Authors

Christoph Molnar is interested in everything to do with machine learning. He is an independent researcher and book author based in Munich, Germany. Before this book, Christoph Molnar has written several other books: Interpretable Machine Learning, Modeling Mindsets, Introduction To Conformal Prediction With Python, and Interpreting Machine Learning Models With SHAP. He also writes a newsletter called Mindful Modeler about machine learning topics beyond pure prediction.

Before Christoph decided to become an independent author, he did his PhD at LMU Munich with Timo on interpretable machine learning. Between his PhD and his Bachelors & Masters in Statistics at LMU, Christoph worked several years as a statistician and data scientist. In his spare time, Christoph enjoys cycling & calisthenics, shopping for groceries, cooking & eating delicious food, reading sci-fi novels by Liu Cixin & qntm, and ice bathing. You’ll find him on Twitter, LinkedIn, and his personal website.

Timo Freiesleben is genuinely curious about machine learning and the philosophical questions it raises. Timo is a strange mix of a philosopher of science and a machine learning researcher. He is currently a post-doc at the “Machine Learning for Science” cluster at the University of Tübingen. Here are links to his website and his Google Scholar profile. In his spare time, Timo enjoys hiking, cooking, reading strange things like Dostoyevsky & Kafka, doing creative things like drawing & poetic writing, sports like football, skating, & stand-up-paddling, and, like most people, spending quality time with friends & family.

Before his current position, Timo did his PhD with Christoph at LMU Munich, working mainly on interpretable machine learning, scientific modeling, and causality. He studied philosophy of science, mathematics, machine learning, and neuroscience at LMU Munich and the University of Tübingen – so he practically changed faculties every two years. Timo is currently part of the Carl Zeiss Foundation project “Certification and Foundations of Safe Machine Learning Systems in Healthcare,” which also funds his postdoc position.