The GrapheneX–UTS Human-centric AI Research Centre (HAI) was formed by an enthusiastic individual who firmly believes in the potential of AI to serve humanity and places the human at the centre of its development.
The visionaries behind the formation of HAI
GrapheneX, a leading industry partner, partnered with UTS to establish the GrapheneX–UTS Human-centric AI Research Centre (HAI), which aims to advance Industry 5.0 by combining human creativity and ingenuity with AI and automation for a sustainable and resilient industry. The partnership between GrapheneX and UTS emphasises the importance of collaboration between research organisations, universities, and industries to bridge the gap between innovation and commercialisation. The team comprises experts in frontier materials, advanced manufacturing, digital, and AI sectors to translate ideas into products and transform traditional industries with digital technologies.
Leadership team
Distinguished Professor CT Lin
Director, Human-centric Artificial Intelligence Centre
Today, in human-AI teaming specific tasks are usually assigned to either humans or AI. This works well if clear boundaries in the interaction between humans and AI exist, allowing clear task assignment. Where the boundary is fuzzy – in evolving and ambiguous situations or where the collaboration is developing and changing – specific task assignment is highly challenging.
HAI has set out to overcome these challenges to develop human-AI teaming for applications where reliability, precision, safety and speed are paramount. In true human and AI teaming, expanding and complementing human and artificial intelligence results in adaptive and spontaneous cooperation. The key to achieving this potential is co-learning which endows AI and humans with teaming intelligence.
Dr Thomas Do
Co-Director, Human-centric Artificial Intelligence Centre
Steering committee
UTS
GrapheneX
- Stephen Wee
- Dr Matthew David
HAI members
Trustworthy human-autonomy teaming (tHAT)
Team Lead: Dr Fred Chang
Spontaneous autonomous swarm intelligence (sASI)
Team Lead: Dr Khuong Tran
Natural brain-computer interface (nBCI)
Team Lead: Dr Thomas Do