C | Autonomous Trucks Stream | Case Study
Tuesday, March 18
08:30 AM - 09:00 AM
Live in Berlin
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As the sophistication of AV increases, the need for comprehensive validation methodologies become imperative to ensure their safety and reliability in diverse real-world conditions. Visual Language Models, powered by state-of-the-art deep learning techniques, have exhibited remarkable capabilities in understanding and generating rich textual content from visual inputs. By harnessing the synergy between natural language processing and computer vision, VLMs enable efficient search through large amount of driving data while simultaneously providing rich description and the possibility to identify interesting driving scenarios that can be used to test the AV stack in simulated environment, potentially revolutionizing the validation process of AD systems.
M.Sc. in dependable aerospace system. Have been working with autonomous systems during university time within the defense industry. Continue my career at Traton Autonomous Transport Solution working with autonomous trucks within the field of VoV, SIL and machine learning.
What drives you? Why do you love your job?
I love working within this field of cutting-edge technology and especially withing Safety and VoV for autonomous driving. I feel honored to be part of the community that is going to set the standard for how we validate the autonomous systems, perhaps one of the most important work withing this tech area and also highly important for the trust of our systems from the society. It is also intriguing to apply ML techniques to find solutions within this area that historically has been driven by traditional methods.