Yao Qu

Yao Qu

Ph.D. Candidate in Public Policy and Global Affairs at Nanyang Technological University. Email: yao008@e.ntu.edu.sg

Hi, I am Doris Yao Qu ( 瞿瑶 )

I am a Ph.D. Candidate in Public Policy and Global Affairs at Nanyang Technological University (NTU), Singapore, supervised by Prof. Jue Wang. My research interests include Generative Artificial Intelligence in Education, Technology Adoption and Ethics, Education Policy, Innovation Governance, Knowledge Practices, and Academic Integrity. I am passionate about leveraging AI to address complex societal challenges and improve the decision-making process in governance and higher education.

Education

  • Ph.D. Candidate, Nanyang Technological University (NTU), Singapore (Aug 2022 – Present)
    • Research Focus: Technology Acceptance, AI Simulation for Public Policy
  • Open Fellowship Program, Weizenbaum Institute, Berlin, Germany (Mar 2025 – Jul 2025)
    • Research Project: AI Academia: Mapping the Transformation of Learning and Research Practices in the Digital Age
  • Master of Philosophy, University of Cambridge, UK (Aug 2021 – Aug 2022)
    • Focus: Urban and Environmental Planning, Urban and Housing Policy
  • Bachelor’s Degree, Sichuan University, China (Sep 2017 – Jun 2021)
    • Major: Economics

Publications and Working Papers

  1. Qu, Y., & Wang, J. (2024). Performance and biases of Large Language Models in public opinion simulation. Humanities and Social Sciences Communications, 11(1), 1–13. https://doi.org/10.1057/s41599-024-03609-x (IF: 3.7, JCR Q1)

  2. Qu, Y., Tan, M.X.Y., & Wang, J. (2024). Disciplinary differences in undergraduate students’ engagement with generative artificial intelligence. Smart Learning Environments, 11(1), 51. https://doi.org/10.1186/s40561-024-00341-6 (IF: 4.8, JCR Q1)

  3. Qu, Y., & Wang, J. (2025). The impact of AI guilt on students’ use of ChatGPT for academic tasks: Examining disciplinary differences. Journal of Academic Ethics. https://doi.org/10.1007/s10805-025-09643-x (IF: 2.2, JCR Q1)

  4. Tan, M.X.Y., Qu, Y., & Wang, J. (2025). Student perceptions of generative artificial intelligence regulations: A mixed-methods study of higher education in Singapore. Higher Education Quarterly, 79(3), e70038. https://doi.org/10.1111/hequ.70038 (IF: 2.8, JCR Q1)

  5. Qu, Y., Loo, H.E., & Wang, J. Generative Artificial Intelligence in Higher Education: Emotional Tensions and Ethical Declaration. Manuscript under review

Ongoing Projects

  • To What Extent and How Do Scientific Structures and Practices Shape the Use of Generative Artificial Intelligence?
    • A large-scale international survey of 10,000 scholars to investigate the adoption and perception of generative AI across disciplines.
  • Simulating Stakeholder Interactions in Policy Making Using Large Language Models
    • Leverages LLMs to simulate stakeholder interactions in policy-making, addressing challenges like inclusivity and equity.
  • Authorship and Accountability in the Age of GenAI: Evidence from PhD Students
    • A survey experiment studying how PhD students assign credit and responsibility when using GenAI, and how competitive academic environments influence disclosure decisions.