Dat is the Head of AI at Axel Springer Ideas Engineering, the innovation unit of Axel Springer SE which is the largest digital publishing house in Europe. He establishes and leads Axel Springer AI where his goal is to make AI more accessible within Axel Springer and hence drive innovations within the group. His ultimate plan is to turn Axel Springer into an AI first company.
Previously, he co-headed the data team at idealo.de where he built up the machine learning team from scratch. His team mainly focused on computer vision problems from teaching a computer to understand aesthetics to upscaling low-resolution images.
He is a regular speaker and has presented at several renowned conferences. He also blogs about his work on Medium. His background is in Operations Research and Econometrics. Dat received his MSc in Economics from Humboldt University of Berlin.
Dat’s interests are diverse from traditional machine learning, deep learning, AI in general to computer vision.
Day 1 - Tech Talks 28 May
Lean AI – How to Implement a Production-Ready Deep Learning Model in Twelve Weeks
Many data science and machine learning projects fail which then cause high risks for companies. In product development, there is a concept though called “lean startup” which is all about minimizing risks. In this talk, I will present how lean concepts can be used for ML projects and how both of them are actually very related to each other. I will also present a project that we’re currently working on where we applied those ideas.