Symposium on Artificial Intelligence – Machine Learning in Safety Critical Systems

Oct 21, 2021 4:00 PM - Oct 22, 2021 8:00 PM India Standard Time

INCOSE India, in collaboration with IEEE Systems Council Bangalore Chapter and Aeronautical Society of India, is organizing this virtual symposium to bring together experts from multiple sectors such as aerospace and automotive, to share their research findings and experiences on various challenges pertaining to adoption of AI-ML in safety critical systems.

Artificial Intelligence for Systems Engineering - AI4SE 2021
Machine Learning in Safety Critical Systems

Location: Virtual
Dates: 21-22 October 2020
Time: 16:00 - 20:00 Indian Standard Time (UTC +5:30)
Registration: https://www.aesievents.com/registration

INCOSE India, in collaboration with IEEE Systems Council Bangalore Chapter and Aeronautical Society of India, is organizing this virtual symposium to bring together experts from multiple sectors such as aerospace and automotive, to share their research findings and experiences on various challenges pertaining to adoption of AI-ML in safety critical systems.

There is an increasing demand for safety critical engineered systems to inculcate humanlike-intelligence and autonomy through adoption of Artificial Intelligence (AI) models, including data-driven decision making capabilities based on machine-learning (ML) algorithms and techniques. This demand is exponentially increasing the complexity in the design, verification, and validation of such safety critical intelligent systems that are subjected to regulations and certifications.

Engineering such systems requires an assurance on the behavior and performance of the system, and may require new approaches in arriving at the system design, in ensuring that the system is ready for operations, and in engineering safe and effective human interaction with intelligent systems. Challenges include new failure modes (e.g. negative side effects, unsafe exploration), unpredictability (e.g. performance on unseen data), trust and robustness (e.g. explainable decisions and behavior).

This symposium aims to bring together experts from multiple sectors such as aerospace, automotive, industrial automation and healthcare to share their research findings and experiences on various challenges pertaining to adoption of AI-ML in safety critical systems, including implications on regulations and certification.

See the Flyer for more details