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Dependable Intelligent System

Developing Reliable and Safe Technologies for Intelligent Systems

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The DEIS Research Group at the University of Hull is at the forefront of pioneering work in Dependable Intelligent Systems — advanced intelligent systems whose failure could pose serious risks to people, the environment, the economy, and society.

These systems span a wide range of applications, including autonomous vehicles, multi-robot systems in healthcare and industrial automation, drone swarms for infrastructure maintenance and logistics, as well as machine learning algorithms and generative AI supporting a diverse set of tasks.

The inherent Complexity, Intelligence, Autonomy, and Openness of these systems — and broader Systems of Systems (SoS) — introduce substantial challenges for ensuring Dependability, i.e. their safety, reliability, security, and privacy. For over 25 years, the DEIS group has been developing cutting-edge methods and tools to assess and assure the dependability of intelligent systems.

Among our key technologies are HiP-HOPS (Hierarchically Performed Hazard Origin and Propagation Studies) and SafeML (Safety of Machine Learning), which are already commercialised or in the process of commercialisation. These tools are used by leading global organisations such as Honda, Nissan, and NYK Lines in Japan; Huawei in China; Honeywell in the US; Volvo in Sweden; Continental in Germany; Fiat in Italy; and Embraer in Brazil.

The group is led by Professor Yiannis Papadopoulos and co-led by Dr Koorosh Aslansefat.

Technologies

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Unprecedented Velocity. Impeccable Reliability.

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