Gabriele Compostella

Chief Technology Officer, Data Lab Munich, Volkswagen AG


Dr Gabriele Compostella holds a PhD in particle physics and spent more than 10 years as an academic researcher in large international collaborations at Fermilab and CERN, where he studied the properties of elementary particles produced at hadron colliders.
He joined the Volkswagen Data Lab in Munich in 2015, where he is now CTO and serves as Principal Scientist for one of the group’s largest digitalization initiatives, the Digital Production Platform.
His current research interests are focused on the technical challenges behind the industrial implementation of big data analytics, machine learning and applied AI.
e learning and applied AI.

Getting to know...

Our research shows that 82% of data and analytics leaders believe that enterprises that don’t embrace AI will lose market share to their competitors within five years. What are your thoughts on this, Gabriele?

I believe the forecast may even be too optimistic! AI-based technologies have shown their potential to disrupt existing business models and create completely new revenue streams.

Research in the field is progressing at an incredible pace, attracting large investments. Open source software implementations and the availability of cloud-based technologies have lowered the entry barrier for new actors in the market significantly.

Existing enterprises shouldn’t waste time and risk losing ground. They should acquire new talent, innovate their IT landscape and seek applications of AI that build on their data and business understanding in order to keep their competitive advantages.


What technological innovations do you hope to see deployed in the automotive industry in the next 2-5 years?

As all the AI enthusiasts, my dream would be to see a reliable implementation of autonomous driving that is better than humans in any road and traffic condition.

There are also a lot of other ‘smaller’ advancements that would provide value in the short term. For example, AI based driver fatigue and stress recognition, integrated services implementing multimodal mobility, intelligent driving assistants that adapt to weather conditions or systems for large scale traffic flow optimization.

I’m sure we’ll see lots of innovations in the automotive space in the next years.