Solution Study
Monday, June 16
02:55 PM - 03:25 PM
Live in Berlin
Less Details
Validating in-cabin monitoring systems raises essential questions across the system lifecycle. From development to integration to regulatory compliance, how do we ensure consistency and readiness for real-world use? This session explores the validation process through the lens of data — its generation, quality, and role in meeting diverse stakeholder needs. We have heard about using synthetic data for training, but how consistent and valid is synthetic data for validation? We’ll examine how robust validation pipelines can go beyond regulations to ensure systems that, not only comply, but also perform reliably for the end user.
Key questions that will be addressed:
After graduating in Physics at the Complutense University of Madrid with master's courses at Temple University, I turned to technology and now I have over 30 years of experience in software development, systems integration, project, and product management. I have worked for all kinds of companies, highlighting my time at HP and more recently at Samsung Research, where I had the opportunity to apply all my experience in deep learning-related projects. I’m currently Anyverse's product technical expert and point of contact for applications such as sensor simulation or deep learning training using advanced hyperspectral synthetic data.
What I love about my job: I’m in that rare place where I can create solutions with amazing computer graphics technologies to help AI machine learning models understand reality. How cool is that? I get to work with extremely intelligent people in sectors like automotive that are at the forefront of innovation.