About Me

I am a fourth-year Ph.D. candidate in Computer Science at the INtelligent Data Engineering Lab (INDElab), University of Amsterdam, advised by Prof. Dr. Paul Groth and Dr. Klim Zaporojets.

I am on the job market, seeking Data Scientist and Machine Learning Engineer roles. Feel free to reach out at p.zhang@uva.nl or download my CV (PDF).
Based in Amsterdam · open to roles across the Netherlands

My research builds deep-learning models for multi-modal knowledge graphs that stay accurate as data drifts over time and that disambiguate near-identical entities. I fuse graph structure, text, images, and temporal signals for entity linking, link prediction, and recommendation. My methods consistently improve over prior state of the art (up to +20% on entity linking and +6% on recommendation) and ship as open-source code with released datasets and benchmarks.

Before joining UvA, I received my Master’s degree in Control Engineering from Beijing University of Technology in 2022, advised by Prof. Dr. Yong Zhang, where I worked on graph neural networks under power-law distributions and multi-view graph representation learning.

Education & Awards & Service

Education

2022 - Present: Ph.D. in Computer Science, 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

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).