Contact Information

Name
Danila Pavliuk
Professional Title
Research Assistant at Institute of Education, HSE University
Email
dpavlyuk@hse.ru
Location
Moscow, Russia
University Profile
HSE University

Higher education researcher studying doctoral education, supervision, and institutional conditions for early-career researchers. I combine quantitative analysis of surveys and digital traces with qualitative interview experience to understand how universities can make entry into research more supportive.

Position

  • Research Assistant

    Institute of Education, HSE University

    2023 - present
    Moscow, Russia

Education

  • HSE University

    BA, Public and Municipal Administration

    2026
    Moscow, Russia

Publications

  • Pavliuk, D. (2026). Do thesis topics matter? How thesis topic characteristics relate to doctoral experience and self-confidence in defence. Higher Education. (link)
  • Pavliuk, D., & Zhuchkova, S. (2025). Choosing to succeed? Insights into doctoral students' supervisor selection and its outcomes. PLOS ONE. (link)
  • Zhuchkova, S., & Pavliuk, D. (2024). Doctoral education as a priority? Improving doctoral education as part of Priority-2030 university development programmes. University Management: Practice and Analysis. (link)
  • Gorbunova, E., Mayukova, E., Ovakimyan, E., & Pavliuk, D. (2024). Difficulties of integration as a reason for dropout among student olympiad winners. Voprosy obrazovaniya / Educational Studies Moscow. (link)

Grants and Projects

Conference Presentations

2026

  • Quality in Postgraduate Research (QPR)

    Presentation: Do thesis topics matter? How topic characteristics shape doctoral experience and confidence in defence

    Adelaide

  • Quality in Postgraduate Research (QPR)

    Presentation: Coffee, “small favors”, and power: where should doctoral supervision draw the line? Evidence from paired surveys in Russia

    Adelaide

2025

  • 2025 International Conference on Artificial Intelligence and Education (ICAIE)

    Presentation: Practices and correlates of using generative AI in doctoral education: a comparative case study in China and Russia

    Suzhou

  • The European Conference on Educational Research (ECER 2025)

    Presentation: Previous Interactions Matter: Exploring the Link between Advisors’ Reasons to Supervise and Doctoral Student Outcomes

    Belgrade

  • XVI International Conference of Higher Education Researchers

    Presentation: Reform of academic certification in Russia: assessing dissertation quality in organizations with the right to award academic degrees independently

    Moscow

  • XVI International Conference of Higher Education Researchers

    Presentation: Where is the boundary? Informal relationships between doctoral students and supervisors in Russian universities

    Moscow

2024

  • XV International Russian Conference of Higher Education Researchers “Higher education: balancing efficiency and well-being”

    Presentation: What does it mean to be a doctoral supervisor?

    Moscow

  • III Tomsk International Forum “Transformation of Education”

    Presentation: The landscape of doctoral supervision in Priority-2030 universities: requirements for supervisors and their declared functions

    Tomsk

2023

  • XIV International Conference of Higher Education Researchers “Student experience in the modern university: from applicant to graduate”

    Presentation: Old challenges and new solutions: where is doctoral education moving in Priority-2030 universities?

    Moscow

  • ERAS International Conference and WERA Focal Meeting 2023

    Presentation: Successful Without Experience: What Factors Assist PhD-Students Without an Academic Background Defend a Dissertation

    Singapore

Intellectual Property

No. Registration No. Type Title Registration Details Authors
1 6.0122-2025 Database Database of scientometric productivity indicators of doctoral degree applicants in Russia for 2015-2024, obtained through automated analysis of candidate dissertation abstracts and aggregated at the organizational level. Danila M. Pavliuk

Skills

# Research methods: survey data analysis, econometric modelling, quantitative content analysis, non-reactive digital traces, web scraping, and semi-structured interviews.

Languages

  • Russian: Native
  • English: Professional working proficiency

Interests

Higher education: doctoral education, supervision, early-career researchers, and university development programmes.

Identifiers