Applied Artificial Intelligence Innovation Centre
The Applied Artificial Intelligence Innovation Centre was formed in December 2024 by strategic partners the University of Huddersfield and TWI, based on their mutual goal of accelerating innovation and knowledge transfer in relation to the application of artificial intelligence (AI).
The University of Huddersfield has a long standing reputation for producing high quality, international research output with excellent impact, recognising the importance of looking beyond academia to address global challenges and make a real difference.
AI is an area of computer science that involves building smart machines that are able to perform tasks which usually require human intelligence. Recent advances in AI technologies are now being explored and deployed in a wide range of industries. The Applied Artificial Intelligence Innovation Centre will target the development and deployment of new technologies in relation to autonomous systems, planning and decision making, ML, visualisation and the application of AI.
Objectives
- Generate research and technology capability in the field of applied AI
- Undertake joint research programmes and secure a portfolio of research funding from external sponsors
- Create a collaborative environment between higher education institution and research and technology organisation with substantial research, impact and adoption by industry (HEI-RTO-Industry)
- Develop the next generation of applied AI experts
Core areas
- AI-enabled automated planning for cyber security, supply chains, mental health and well-being, urban traffic management and more
- Application of AI technologies – machine learning, big data, predictive analytics, Internet of Things (IoT), Industry 4.0 and Industry 5.0, smart homes
- Cyber security – identity and access control systems, intrusion and digital forensics
- Augmented and virtual reality, data visualisation
- High performance data analytics
- Computing – service-orientated, infrastructure, cloud, sustainability
- Autonomous systems
- Risk management – delay prediction, cause analysis
- Sustainable software engineering