Complexity
Large systems include many interacting components, extensive software and automation layers. DEIS studies how new failure modes emerge across these interactions.
Research centre
Dependable Intelligent Systems
Developing reliable and safe technologies for intelligent systems whose failure could affect people, the environment, the economy and society.
About DEIS
Dependability research for the next generation of intelligent systems.
The Dependable Intelligent Systems Research Centre at the University of Hull studies advanced intelligent systems that must remain trustworthy under real-world uncertainty. Its work spans autonomous vehicles, multi-robot systems, healthcare and industrial automation, drone swarms for maintenance and logistics, machine learning and generative AI.
DEIS focuses on the assurance challenge created by systems that are complex, intelligent, autonomous and open. The group develops methods and tools that help engineers assess hazards, understand failure causes and improve designs before risks become unacceptable.
Research
The CIAO challenge
Modern intelligent systems stretch classical dependability methods because they combine large-scale software, learned behaviour, autonomy and open operating environments.
Intelligence
Machine learning systems learn behaviour from data rather than explicit designs. DEIS researches assurance approaches for imperfect, adaptive and data-driven components.
Autonomy
Autonomous systems may face unforeseen hazards without immediate human intervention. The group works on safer decision-making and runtime assurance.
Openness
Cooperative Systems of Systems form changing configurations in the field. DEIS develops approaches for assurance beyond closed, fully known designs.
Technologies
Methods, tools and platforms
The centre builds and applies practical technologies for dependable AI, safety engineering and model-based assurance.
HiP-HOPS
Hierarchically Performed Hazard Origin and Propagation Studies supports safety analysis for complex engineered systems, including automated generation of safety artefacts from system models.
SafeML
SafeML focuses on the safety of machine learning, including dataset, model and runtime assurance issues that affect trustworthy deployment.
EDDI Editor
EDDI supports dependability modelling and conversion workflows used in safety and reliability analysis research.
XWHY
XWHY supports explainable AI research by helping users understand, question and communicate model behaviour in trustworthy intelligent systems.
People
Research team
DEIS brings together academic leads, lecturers, researchers and doctoral researchers working across safety engineering, trustworthy AI, software systems and autonomous technologies.
Yiannis Papadopoulos
Lead | Professor of Computer Science
Researches safety and dependability of complex and AI-enabled systems.
Koorosh Aslansefat
Co-Lead | Assistant Professor
Works on dependable AI, explainability and anomaly detection in intelligent systems.
David Parker
Senior Lecturer
Works across software engineering, computing education and academic leadership.
Zhibao Mian
Lecturer in Computer Science
Research interests include safety engineering, trustworthy AI and advanced computing systems.
Kay Atefi
Assistant Professor
Focuses on cybersecurity, innovation and dependable intelligent systems practice.
Connor Walker
PhD Student
Works on data-driven intelligent alarm systems for offshore wind maintenance.
Razieh Arshadizadeh
PhD Candidate
Researches runtime safety and security, Systems of Systems, Edge AI and federated learning.
Louis Donaldson
PhD Student
Works across computer science, distributed systems and applied artificial intelligence.
Ayoola Adowu
PhD Researcher
Researches hallucination mitigation for LLM-based autonomous driving scenario generation.
Mahmoud Asgari
Researcher
Researcher in artificial intelligence.
Impact
Methods used by global engineering organisations.
DEIS technologies have been commercialised or prepared for commercialisation and have been used by leading organisations in automotive, aerospace, industrial automation and safety-critical engineering.
- Honda
- Nissan
- NYK Lines
- Huawei
- Honeywell
- Volvo
- Continental
- Fiat
- Embraer
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Work with the Dependable Intelligent Systems Research Centre.
Academic and research enquiries
For questions about the centre, PhD opportunities, MSc by Research supervision or collaboration, contact Professor Yiannis Papadopoulos.
Email Yiannis PapadopoulosCentre contact
Dependable Intelligent Systems Research Centre, University of Hull, Cottingham Road, Hull, HU6 7RX, United Kingdom.