Advanced Methods of Certification (AMC)

Enabling the safe usage of AI in aerospace systems

Open Positions

If you are interested in exploring potential opportunities to work together, please contact me (Prof. Daw) with a brief statement about how we might collaborate and your CV.

Mission Statement

Flying has been one of the safest modes of transportation for decades. This important achievement can be attributed to the certification processes that push for high quality standards throughout the development, testing, operation, maintenance and inspection of aircraft. We are currently at a tipping point where new technologies such as AI could revolutionize the aerospace industry. Unmanned aerial vehicles are already a reality. Autonomous delivery drones, flying taxis and similar applications could soon follow. However, due to safety concerns, such technologies have rightly not yet been adopted in the aerospace industry. However, there are many efforts by the FAA, EASA, NASA and other government agencies to create certification standards to ensure these technologies are airworthy.

In the AMC Lab, we work on engineering methods for development of AI-enabled systems that are safe, secure and reliable enough for being used in a safety-critical application, in other words certifiable. Our work is based on three areas: The first involves shifting the system specification paradigm from function-driven to data and learning properties-driven for data-intensive applications. The second area addresses building assurance of an AI-enabled system from data selection, through training, coding, testing, operation to the evolution. Furthermore, this area also comprises of building continuous assurance by creating system mitigation strategies. The third area entails the creation of an engineering solution based on the other research areas advances that make AI-enabled systems certifiable.

This image shows Zamira Daw

Zamira Daw

Prof. Dr.-Ing.


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