Christian Winkler is a data scientist and machine learning architect who has spent two decades turning very large collections of text into usable knowledge. He holds a PhD in theoretical physics, a training that shows in his approach to machine learning: rigorous, quantitative, and grounded in the mathematics underneath the models rather than the hype around them.

For 20 years, Christian has worked in the field of large data volumes and artificial intelligence, with a particular focus on scalable systems and intelligent algorithms for mass text processing. That combination of scale and language is notoriously difficult, and it is where he has built his deepest expertise, helping organizations extract structure and insight from document collections that no human team could read on its own.

Christian is the founder of datanizing GmbH, through which he applies this experience to practical text analytics projects. He shares what he learns as a speaker at conferences and as the author of articles on machine learning and text analytics, making him a useful guide for anyone working at the intersection of natural language and big data.