Machine Learning (ML) and Artificial Intelligence (AI) are being used more and more in products. There is interest in using ML in safety critical systems, but most existing safety standards were not written with ML in mind.
As the functional safety community waits for guidance from standards on using ML in safety critical tasks, exida is developing a ML assessment scheme.
This webinar will provide an overview of exida’s ML assessment scheme and exida’s planned ML service offerings.
- Assessment against rigorous design process requirements, and
- ML statistical performance analysis, based on Dr. O’Brien’s PhD thesis.
Dr. O’Brien is a Senior Safety Engineer who performs System FMEAs, Electrical FMEAs, and Electrical FMEDAs for exida Certification. She also performs Hardware and Software certification assessments. Molly is part of a team of experts at exida who are developing a certification scheme for Safety Functions that include Machine Learning. Molly defended her Ph.D. in Computer Science at Johns Hopkins University, and her doctoral thesis focuses on predicting Neural Network performance in novel operating domains. She has research experience in perception, robotics, and medical imaging. Molly received a Bachelor of Science in Electrical Engineering and a Bachelor of Science in French and Francophone Studies from Pennsylvania State University.