Personal profile


I am a PhD student in the Natural Language Processing and Text Mining group. My research focuses on how to summarise medical arguments in social media.

Argument mining is an exciting new field that could have far-reaching implications for fact-checking, decision-making, marketing, legal judgements and more. However, due to its meticulous and logical nature, it is still an open challenge to summarise a large number of arguments effectively. The Knowledge Graph, because of its inherent strengths, allows for the incorporation of rich common knowledge and contextual content into the model. This offers the possibility to assess the quality of arguments and to produce high-quality summaries of arguments.

My research will focus on how argument knowledge graphs can be used to guide the generation of high-quality arguments and the design of automated evaluation methods to advance the field of argumentation mining.

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

Education/Academic qualification

Master of Computing, MSc Advanced Computer Science (Artificial Intelligence), University of Leeds

5 Aug 201915 Nov 2020

Award Date: 15 Nov 2020

Areas of expertise

  • QA75 Electronic computers. Computer science


  • Argument mining
  • Argument summarization
  • Knowledge graph
  • Natural Language Processing
  • Text mining


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