Deliver
- How can AI automatically manage CX to enable a seamless and personalised experience?
- What organisational, technological, and human factors enable or inhibit the adoption and scaling of AI agents across different business contexts?
- How can autonomous AI agents be orchestrated to maximise organisational value while mitigating risks associated with user scepticism or unchecked enthusiasm?
Research Topics
Research Topics under 'Deliver'
Name: Bingxin Yan, Research Associate
Dr. Bingxin Yan’s research focuses on developing AI agent systems for service delivery by integrating multimodal data and statistical and machine learning methods to enable personalized service delivery.
Her work includes developing multimodal AI agents that integrate sensor, textual, document, and video data; emotion-aware conversational agents; and predictive maintenance agents, as well as examining their impact on service delivery and operational oucomes. Her research spansboth B2B and B2C service contexts, including manufacturing, healthcare, and sustainable systems.
Name: Yingrui (Ingrid) Xi, PhD Researcher
Yingrui (Ingrid) Xi's research focuses on designing agentic AI systems for business process optimisation in engineering and manufacturing organisations. Her research investigates how organisational decision knowledge can be modelled and transformed into coordinated AI agents capable of supporting autonomous operational decision-making across complex business processes.
Her work combines information modelling, knowledge representation, decision ontologies, large language models, and multi-agent systems to develop AI architectures for optimising end-to-end business processes, with a particular focus on Order Fulfillment and Assemble-to-Order (ATO) environments. Through prototype development and industrial case studies, she aims to establish the architectural principles and technical foundations required for trustworthy, scalable, and value-creating Agentic AI systems.