Deeply embedded with practical research in the community, HALO is positioned to become an influential leader in HAC research and development, driving towards a smarter and healthier society, and help the school and university achieve a leading position in human-AI research.

Leveraging the multidisciplinary team formed and supported by the center, research are organized as follows. 

Human-Centered Design (HCD)

To propose a framework for HAC systems, leveraging three interface types (natural language interactions, visualizations, and data analysis tools) for interactions between humans and AI systems

a.          Adaptive framework for collaboration contracts

b.         NLP and speech recognition with user-aware tools and assistants

c.          Human-centered visualization that adapts to users behaviors and contexts

d.         Human behavior and psychology on AI tools

Individual + AI

To develop foundational HAC elements for enabling and enhancing an individual’s interaction and collaboration with AI systems.

a.          Interpretable and explainable machine learning

b.         Interactive explainable AI models

c.          Context-based symbiotic AI, e.g., ML based on a holistic view of patients

d.         Dynamic assurance monitoring and control of HAC systems

Team + AI

To advance team-AI collaboration by systematically investigating information sharing, preference elicitation, prioritization, and trust in the novel context of team-based HAC.

a.          Information fusion

b.         Collaborative machine learning

c.          Privacy-preserving ML for leveraging large, multi-site data, e.g., federated learning

d.         Planning and schedule for preference elicitation and privacy

Community + AI

To advance the state-of-the-art in HAC systems to assist humans in complex contexts where decisions affect communities and changing social factors can influence the decisions.

a.          Community data fusion

b.         Interactive, multi-grain data exploration

c.          AI assisted community decision making

d.         Fairness, privacy, trust issues for community 

Human-AI interaction and collaboration (HAC) Applications

a.          Healthcare informatics, personal health aide

b.         Clinical decision support, surgical outcome prediction

c.          Chronic disease management

d.         Patient readmission improvement

e.          Homeless assistance