Join us for a one-day conference focused on the synergy between data-driven insights, advanced powertrain technologies, and performance optimization in modern automotive testing. Discover the latest trends, practical case studies, and cutting-edge solutions for the challenges facing today’s automotive industry.
Key Topics & Themes
Evgeniy Novikov
engineering Lead
CARIAD
With over three decades of professional experience across automotive, robotics, and medical software, he specializes in automotive software integration, focusing on Cloud DevOps solutions and Agile project management.
Ahmed Ebada
professor of informatics and AI, senior product manager
BMW Group
Throughout his career, he has successfully led cutting-edge AI initiatives, scaled ML models for production and contributed to AI’s role in reshaping industries. As a startup leader, he actively drives innovation, business growth and AI-powered solutions while engaging in thought leadership and industry discussions.
Huw Davies
senior lecturer centre for future transport and cities
Coventry University
His research interest is the development of the vehicle test environments and performance measures that support transport policy, standards and regulatory activity in the UK, Europe and internationally. He has worked collaboratively with transport system stakeholders in the UK, EU, the Americas, Africa and Asia – including national government, regional authorities, automotive industry, rail industry.
Pudureddiyur Venkataraman Manivannan
professor
Indian Institute of Technology Madras
He is faculty in the department of mechanical engineering at IIT Madras, India. He has been a visiting faculty at TU Kaiserslautern, Germany; University of Nebraska, Lincoln, USA; and University of South Australia, Adelaide, Australia. He is a distinguished recipient of DAAD and Erasmus Mundus Teaching fellowships.
Stoyan Nikolov
test manager and group lead
Bosch
With experience at Johnson Controls and Visteon, he has held roles in system validation, test automation, and team leadership. He previously worked at McLaren Applied Technologies on autonomous driving and connectivity projects. Stoyan applies advanced data analysis techniques, developed through his postgraduate studies in Machine Learning and AI at Columbia University, to extract actionable insights from large-scale test results and support data-driven engineering decisions at scale.