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Personal profile

Research interests

Yuan-Fang Li (李元放) is an Associate Professor in the Department of Data Science & Artificial Intelligence (DS+AI), Faculty of Information Technology, Monash University. He is also the Associate Dean International of the Faculty.

Yuan-Fang's research interests include knowledge graphs, natural language processing, multimodality, and representation learning (embedding) of networks/graphs. Some of the research problems he works on include:

  • Complex question answering over text and knowledge graphs.
  • Knowledge extraction from other modalities: e.g. event/relation extraction from text and scene graph generation from images.
  • Structural & temporal learning on graphs.
  • Question generation from text & knowledge graphs.

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Monash teaching commitment

Yuan-Fang has experience as the Chief Examiner for the following units in the Faculty of IT:

  • FIT4002 Software engineering studio project
  • FIT4004/FIT5171 System validation and verification, quality and standards
  • FIT5138 Advanced Software Engineering
  • FIT3013 Formal specification for software engineering
  • FIT4008 Reading unit
  • Minor thesis, Masters thesis and Honours thesis units

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being
  • SDG 7 - Affordable and Clean Energy
  • SDG 16 - Peace, Justice and Strong Institutions

Education/Academic qualification

Computer Science, Doctor of Philosophy, National University of Singapore

Award Date: 18 Dec 2006

Computer Science, Bachelor of Computing (Honours), National University of Singapore

Award Date: 7 Aug 2002

Research area keywords

  • Knowledge Graphs
  • Natural Language Processing
  • Knowledge Representation
  • Ontologies
  • Semantic Web

Collaborations and top research areas from the last five years

Recent external collaboration on country/territory level. Dive into details by clicking on the dots or