Chris Hammerschmidt

Calling APIs seems easy, but digging in to develop a deeper understanding of how methods work, when to apply them, and how to push their limits can be daunting and confusing.

Having gone from research to industry, I have successfully guided interns, bachelor/master graduates, and Ph.D. students on their path through the field of machine learning.

Currently, I work as co-founder and principal engineer at an early-stage machine learning start-up coming out of my and my colleagues academic research.

Prior to starting my company, I worked as a machine-learning research scientist bringing deep learning methods on tabular data to know-your-customer and anti-money-laundering products in financial institutions.

Before that, I completed my PhD where I developed machine-learning algorithms for reverse engineering software and applied them on software engineering and network analysis tasks.

Throughout my career, I've done commercial data science consulting projects on the side.