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Zheng Fang


My name is Zheng Fang and I'm a fourth-year Ph.D. student at the Department of Computer Science. My supervisors are Prof Rob Procter and Prof Yulan He. My research mainly focuses on the development of topic modeling tools, especially the tools that can benefit sociological research in social data. Besides, I'm also interested in other natural language processing topics.


  • The University of Nottingham, BSc (Hons) in Software engineering in the first class.
  • The University of Warwick, MSc in Data Analytics in the distinction class.


  • 2019-2020, teaching assistant, CS909-15 Data Mining.
  • 2020-2021, teaching assistant, CS910-15 Foundations of Data Analytics.
  • 2020-2021, teaching assistant, CS909-15 Data Mining.


  • China Scholarship Council (CSC).
  • 2020 WPCCS best presentation award in machine learning.


  • Zheng Fang, Yulan He, and Rob Procter. A query-driven topic model. ACL Findings, 2021.
  • Lixing Zhu, Zheng Fang, Gabriele Pergola, Robert Procter, Yulan He. Disentangled Learning of Stance and Aspect Topics for Vaccine Attitude Detection in Social Media. NAACL, 2022.
  • Zheng Fang, Lama Alqazlan, Du Liu, Yulan He, and Rob Procter. A User-Centered, Interactive, Human-in-the-Loop Topic Modelling System. EACL, 2023.
  • Zheng Fang and Du Liu. Identify Patent Value Using Semi-Supervised Topic Modelling: An Application in Synthetic Biology. Presented at 1st Economics of Financial Technology Conference. Also accepted by EPIP, 2022.

Working papers

  • Zheng Fang, Yulan He, and Rob Procter. CWTM: Leveraging Contextualized Word Embeddings from BERT for Neural Topic Modeling. Submitted to EMNLP, 2023.
  • Lama Abdulrahman Alqazlan, Zheng Fang, Robert Procter, Michael Castelle. A Novel, Human-in-the-Loop Framework for Computational Grounded Theory. Submitted to EMNLP, 2023.
  • SyROCCo: Systematic Review of Outcomes Contracts using Machine Learning (with Miguel, Rob, Felix et al). Submitted to Research Synthesis Methods, 2023.
  • Getting more out of Systematic Reviews: How Machine-Learning-enabled Systematic Reviews can Help support Research and evidence-based Policy Making (with Miguel, Rob, Felix et al).

Research Project

  • 2021.12 - 2022.04, Oxford GO LAB, research assistant, "Machine Learning in Support of Systematic Review".
  • 2022.09 - 2023.05, Oxford GO LAB, research assistant, "Systematic Reviews Supercharged: Employing Machine Learning Tools to Support Systematic Review on Outcomes Based Contracting"


Zheng Fang


Room: CS3.27