Data Lifecycle Copilot

Data Copilot for Data Understanding and Visualisation 
  • Focus:
    • Leverage the capabilities of LLM to enable data understanding in a conversational and interactive ways without the requirements of expert knowledge​
  • Objectives​:
    • Knowledge driven data understanding (automatic / QA)​
    • Data story-telling generation​

Contact: Dr Jieshan Chen

LLM-enhanced Data Discovery
  • Focus:
    • Data discovery based on LLM + KG​
    • Data visualisation
    • LLM-based Q&A
    • Responsible Data Management and Governance
    • Most likely the package will be aligned with the existing agricultural protein work
    • As an initial step, it will focus on improving the demo by addressing its limitations

Contact: Dr Yanfeng Shu

Privacy AI CoPilot for Data Sharing
  • Focus:
    • Synthetic Data set generation​
    • Incorporating Responsible AI Principles around privacy, fairness, reliability and explainability​
    • Analytics through MLAI
    • Responsible Data Management and Governance
      • Privacy Preserving Graph Analytics​​
      • Federated Learning​​
      • Foundational Models​

Contact: Dr David Smith

Understanding Data Privacy Risk

Contact: Dr Paul Tyler

Responsible Research Copilot (R2C)
  • Focus:
    • Data & model lineage​
    • Verifiable Credentials & Consent​
    • Identity and Access control​
    • Federated & other privacy-preserving data processing workflows
  • Objectives: To develop a copilot to aid the research data management process by leveraging verifiable Credentials, Consent, LLMs, and data and model lineage technologies.

Contact: Dr Dilum Bandara

Project Manager: Judy Zheng