Panel Discussion
Monday, June 30
06:30 PM - 07:15 PM
Live in San Francisco
Less Details
Received the B.S. and M.S. degrees in aerospace engineering in 2012 and the Ph.D. degree in reliability engineering and system analysis in 2018, both from the Bauman Moscow State Technical University, Russia. From 2012 to 2016, used to be a Reliability Engineer in several major Russian radar and electronics companies. Since 2016, has been a System/Functional Safety Engineer with RoboCV, Russian-based warehouse automation start-up based in Skolkovo Innovation Centre, Moscow. Later in 2017 joined Arrival Ltd., a UK-based electric vehicles start-up where he was in the position of the Head of Functional Safety. Dr. Babaev is the author of more than 25 publications in reliability and safety engineering, as well as 2 patents in automotive and machinery safety areas. His research interests include reliability and safety engineering, system analysis, machine learning and statistics methods in safety. Dr. Babaev is a co-guest Editor of the MDPI 'Artificial Intelligence for Connected and Automated Vehicles' journal. He is also a part of UK ISO 21448 workgroup and TUV Rheinland certified functional safety engineer.
Shafiq Urréhman is a Technical Lead AI/ML & Advisor – Digital Technologies at Zeekr Technology Europe with over 7 years of experience in the automotive industry. He is a results-driven executive with experience in increasing growth in businesses with emerging technologies in international context; skilled in product management with a demonstrated history as transformational leader.
György Katona is a Technical Project Manager at Bosch Hungary, specializing in data-driven solutions for automotive innovation. With over 5 years of experience in the automotive sector, he has led large-scale data management platforms and currently spearheads a project developing tools to streamline data enrichment for machine learning engineers. Passionate about the transformative power of data, György excels in bridging technical gaps between teams, optimizing workflows, and delivering scalable solutions that address critical bottlenecks in ADAS development. His expertise spans data science, AI-driven tooling, and collaborative problem-solving, ensuring robust and efficient ML pipelines for autonomous driving systems.
The Pop in Your Job – What drives you? Why do you love your job?
What drives me is the thrill of turning complex challenges into streamlined solutions. I thrive on collaborating with diverse teams - understanding their pain points, dissecting their workflows, and crafting tools that empower them to focus on innovation. Data isn’t just numbers or algorithms to me - it’s the backbone of safer, smarter autonomous systems. Whether it’s visualizing insights to tell a compelling story or designing AI tools that accelerate development, I love how my work directly impacts the future of mobility.