About Me

I am a final-year PhD candidate in Computer Science at the University of Amsterdam (INDElab), advised by Prof. Dr. Paul Groth and Dr. Klim Zaporojets. My defense is planned for March 2027.

I am on the job market, open to industry roles (Applied Scientist / Machine Learning Engineer / Data Scientist) and postdoctoral positions. Reach me at p.y.zhang3@gmail.com or download my CV (PDF).

  • Multi-modal knowledge graphs
  • Entity linking & resolution
  • Link prediction
  • Recommendation
  • Large language models

I work on machine learning for knowledge graphs, where the data keeps changing and many entities look alike. I build models that add signals which are usually left out, such as how the graph changes and time itself, so that entity linking, link prediction and recommendation stay accurate on sparse, long-tail and look-alike entities. The same problem appears in industry as entity resolution under data drift.

Education

  • 2022 - Present PhD in Computer Science (defense planned for March 2027), INDElab, Faculty of Science, University of Amsterdam (UvA), the Netherlands. Supervisors: Prof. Dr. Paul Groth, Dr. Klim Zaporojets.
  • 2019 - 2022 MEng in Control Engineering, Faculty of Information Technology, Beijing University of Technology (BJUT), China. Supervisor: Prof. Dr. Yong Zhang.

Awards & Service

Awards

  • 2026 Conference travel grant for ACL 2026.
  • 2022 Outstanding Master’s Thesis, Beijing University of Technology.

Service

  • Reviewer / sub-reviewer: CIKM, ECAI, ESWC, PKDD.
  • 2020 - 2021 Teaching assistant, Data Engineering (BJUT).

Skills

Programming

Python, PostgreSQL, Bash, Git, Linux

ML & DL

PyTorch, Hugging Face, scikit-learn, NumPy, Pandas, Large language models, Vision-language models, Graph neural networks, Contrastive learning, Entity linking and resolution, Recommendation

Languages

Chinese (native), English (fluent, IELTS 7.0), Dutch (elementary, A2)