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Qingyun Wang

  • Advisor:
    • Heng Ji
  • Departments:
  • Areas of Expertise:
    • Natural Language Processing
    • AI for Science
  • Thesis Title:
    • AI Scientists: Toward Automated Literature Understanding and Scientific Discovery
  • Thesis abstract:
    • My research interest lies in Automated Literature Understanding and Scientific Discovery. My long-term vision is to expand AIScientist to augment the process of scientific paper lifecycle by equipping machines with the ability to understand scientific papers, propose new ideas, conduct experiments, write paper drafts , and evaluate the final paper drafts. This encompasses three threads (but are not limited to): (1) Constructing Scientific Knowledge Graph with Limited Annotated Data (Examples: Multimedia KG for Covid-19 (NAACL ‘21 Best Demo🏆), Few-shot Chemical Entity Extraction); (2) Scientific Hypothesis Discovery through Knowledge Fusion (Examples: Scientific Hypothesis Generation, Procedure Prediction); and (3) Applying Knowledge Graph (Examples: Paper Review Generation, Data-to-text Generation)
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Contact information:
qingyun4@illinois.edu