About Me

I am a final-year Ph.D. candidate in Computer Science at the University of Amsterdam (INDElab), advised by Prof. Dr. Paul Groth and Dr. Klim Zaporojets. I expect to defend my thesis in 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 use signals others ignore, such as how the graph evolves and time itself, so entity linking, link prediction and recommendation stay accurate on sparse, long-tail and look-alike entities. In industry terms, this is entity resolution and matching under data drift.

Education

  • 2022 - Present Ph.D. in Computer Science (expected 2027), INDElab, Faculty of Science, University of Amsterdam (UvA), the Netherlands. Supervisors: Prof. Dr. Paul Groth, Dr. Klim Zaporojets.
  • 2019 - 2022 M.Eng. 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)