BEGIN:VCALENDAR VERSION:2.0 PRODID:-//DATE2026//date-conference.com//EN CALSCALE:GREGORIAN METHOD:PUBLISH BEGIN:VEVENT DTSTART;TZID=Europe/Rome:20260422T140000 DTEND;TZID=Europe/Rome:20260422T153000 LOCATION:Room Auditorium CREATED:20260421T174602 DTSTAMP:20260421T174602 SUMMARY:FS09 Focus Session: Autonomous Systems Dependability in the Era of AI - Design Challenges in Security, Reliability and Certification URL;VALUE=URI:https://date26date-conference.com/programme#FS09 BEGIN:VALARM TRIGGER:-PT15M ACTION:DISPLAY DESCRIPTION:Reminder END:VALARM DESCRIPTION:Get the latest session information at https://date26date-conference.com/programme#FS09\n\n\nThe design of embedded safety-critical systems such as those used in next-generation automotive and autonomous platforms, is increasingly challenged by escalating system complexity, hardware–software heterogeneity, and the integration of intelligent, data-driven components. Ensuring dependability in such systems requires a holistic approach that spans multiple abstraction layers and encompasses both design-time and run-time assurance. Traditional methods for reliability, safety, and security management often fall short in addressing the dynamic and uncertain behaviors introduced by Artificial Intelligence (AI) and Machine Learning (ML) components, especially under stringent real-time, power, and safety constraints. While AI and ML offer powerful predictive, adaptive, and self-optimizing capabilities that can enhance system dependability, their inherent non-determinism, data-dependence, and lack of formal guarantees introduce new challenges for verification, validation, and certification. This session will explore emerging methodologies, architectures, and frameworks for designing dependable autonomous and embedded systems in the era of AI. It will highlight advances in reliability modeling, secure system design, and certification approaches that account for imperfect, learning-enabled components, aiming to bridge the gap between AI innovation and certifiable system-level dependability. X-ALT-DESC;FMTTYPE=text/html:

Get the latest session information at https://date26date-conference.com/programme#FS09

The design of embedded safety-critical systems such as those used in next-generation automotive and autonomous platforms, is increasingly challenged by escalating system complexity, hardware–software heterogeneity, and the integration of intelligent, data-driven components. Ensuring dependability in such systems requires a holistic approach that spans multiple abstraction layers and encompasses both design-time and run-time assurance. Traditional methods for reliability, safety, and security management often fall short in addressing the dynamic and uncertain behaviors introduced by Artificial Intelligence (AI) and Machine Learning (ML) components, especially under stringent real-time, power, and safety constraints. While AI and ML offer powerful predictive, adaptive, and self-optimizing capabilities that can enhance system dependability, their inherent non-determinism, data-dependence, and lack of formal guarantees introduce new challenges for verification, validation, and certification. This session will explore emerging methodologies, architectures, and frameworks for designing dependable autonomous and embedded systems in the era of AI. It will highlight advances in reliability modeling, secure system design, and certification approaches that account for imperfect, learning-enabled components, aiming to bridge the gap between AI innovation and certifiable system-level dependability.
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