University home | Studying | Research | Business and community | Working here | Alumni and supporters | Our departments | Visiting us | About us

• Homepage
• Key Information
  • Almanac
  • Building Access
  • Building Maps
  • College Policies
  • College Structure
  • Key Academic Roles
  • Academic Groups
  • Key Professional Service Contacts
  • Staff Profiles
    • Academic Staff
    • Research Staff
    • Postgraduate Research Students
    • Professional Services Staff
    • Honorary Staff and Visitors
    • All Staff
  • Events and Colloquia
  • Useful Links
• Students
• Staff
• PGR
• Health and Safety
• Computer Support
• National Student Survey (NSS)
• Intranet Help

Dr Hang Dong

• Profile
• Publications

Dr Hang Dong

Lecturer in Computer Science (E&R)

Location: Innovation Centre Phase 1 G1

Telephone: 01392 726654

Extension: (Streatham) 6654

Hi, I am Hang! Most recently before joining Exeter as a lecturer, I was a senior research associate in Computer Science at the University of Oxford from 2022 to early 2024, working on Ontology Enrichment with Natural Language Processing for the EPSRC project (ConCur). Before this, I was a research fellow in health informatics at Usher Institute, University of Edinburgh, for the Health Data Research UK projects (text analytics), for over 2 years till 2021, which was timely when COVID-19 arrived. I had a doctoral degree in Computer Science at the University of Liverpool in 2020, working on knowledge discovery from text data, an MSc and a Bachelor's degree in the Information School at the University of Sheffield and Wuhan University, respectively.

My research interests include and are not limited to (with open access links to previous work):

• Machine learning for data, texts and structured knowledge: using machine learning and, especially, deep learning methods for text mining, information extraction, entity linking, classification, with a semantic structure, and ontology enrichment from texts and user-generated data. These tasks transform unstructured data into a structured form.
• Integrating Language Models and structured knowledge: exploring ways to support the knowledge reasoning capability of Language Models (for example, BERT variants and GPT series) by using human curated knowledge graphs, for example, ontologies or domain-specific concepts and relations in the healthcare domain.
• Healthcare text analytics and AI applications: Natural Language Processing, multimodal learning, with key applications in automated clinical coding and disease phenotyping, by integrating unstructured and structured data, and visual language understanding in medical data, to support healthcare service and clinical decision-making. A key focus is the explainability of models by integrating knowledge with unstructured data.

Editorial service:

I am an editorial board member for Transactions on Graph Data and Knowledge (TGDK). Also, I have been reviewing for top conferences and journals, including ACL Rowling Review, WWW, ISWC, ESWC, CIKM, IJCAI, FAccT, IEEE Trans. Med. Imaging, J. Biomed. Inform, J. Web Semant., IEEE Trans. Neural Netw. Learn. Syst., etc.