Machine learning/deep learning
Conduct research on state-of-the-art machine learning, deep learning, large language models and their applications in agriculture, finance, health, etc.
AI ethics/AI for social good
We aim to offer a framework to identify, implement, and validate ethical principles of AI to make ethics of AI operationable in real-world applications.
AI Fairness
We explore fairness of AI solutions from perspectives of data, model, and outcomes, as well as evaluation approaches for AI fairness.
AI Explainability
We investigate advanced AI explanation approaches and develop explanation evaluation methods to enhance trust and usability of AI explainations
AI Security
We investigate the security of AI model and its explanations with various attack and defence approaches.
Visual Analytics
We integrate visualisatons with machine learning approaches into data analytics pipeline to visually interact with data and analysis outcomes.
Multimodal Behaviour Analytics
Human behaviour changes can be reflected from human’s multimodal responses including behaviour and physiological responses. We have solid skills in multimodal data-driven analytics to understand complex human behaviours.
Physiological and behavioural sensing
We have more than 10 years of experience with analysing data from eye-activity, galvanic skin response, EEG, mouse movements and other signals to cast light on cognitive states such as stress, emotional arousal, etc.
User trust in machine/AI
Research on human factors in human-machine interactions, pioneering cognitive load modeling and trust assessment using multimodal behavior and physiological signals.
Cognitive load measurement
Conduct world leading research in robust cognitive load measurement using multimodal behavior and physiological signals.