Abstract

The mission of Zenseact is to develop a world-leading autonomous driving software platform for consumer vehicles, with the primary goal of dramatically reducing the number of traffic fatalities and injuries around the world. I will discuss how we use deep learning to reach this goal, some of the key challenges we see, and how we plan to expand the use of learning-based algorithms. I will also review some of our recent and ongoing deep learning-related research activities.

Christoffer Petersson

AI Researcher @ Zenseact

On the research side, Christoffer Petersson leads and supervises a number of deep learning-related research activities at Zenseact and is Adjunct Associate Professor in Machine Learning at Chalmers. On the product side, he works towards expanding the use of deep learning in the Zenseact software stack and automating the training data generation. Christoffer did a PhD in Theoretical Physics at Chalmers, and after research positions in Physics at CERN, in Madrid and Brussels, and returning to Chalmers as Associate Professor in Physics, he switched gears and joined Zenuity (from which Zenseact originates) in 2017 and has since then worked on deep learning and computer vision in both product development and research.