Personal profile

Chinese Name

杨任驰

Biography

Dr. Yang received his BEng degree in software engineering from Beijing University of Posts and Telecommunications and his PhD degree in computer science from Nanyang Technological University. Prior to joining HKBU, he was a postdoctoral research fellow at the National University of Singapore. His research focuses on developing efficient algorithms and systems for large-scale data management and analysis. His research works have been published in top-tier data management and data mining conferences/journals including SIGMOD, VLDB, TODS, KDD, WWW, etc. He received the VLDB 2021 Best Research Paper Award, the 2022 ACM SIGMOD Research Highlight Award, and the Best Paper Award Nominee in WWW 2022.

 

Research Interests

  1. Databases and data management: graph query processing, similarity search
  2. The Web and information retrieval: search and ranking, recommendation, web mining
  3. Data mining and machine learning: social network analysis, graph representation learning

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 4 - Quality Education
  • SDG 8 - Decent Work and Economic Growth
  • SDG 9 - Industry, Innovation, and Infrastructure
  • SDG 16 - Peace, Justice and Strong Institutions

Education/Academic qualification

PhD, Computer Science, Nanyang Technological University

23 Jul 201631 Jan 2021

Award Date: 31 Jan 2021

Bachelor, Software Engineering, Beijing University of Posts and Telecommunications

15 Aug 201115 Jun 2015

Award Date: 15 Jun 2015

Keywords

  • QA75 Electronic computers. Computer science
  • QA76 Computer software

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Dive into the research topics where Renchi YANG is active. Topic labels come from the works of this scholar.
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Collaborations and top research areas from the last five years

Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
  • Adaptive Local Clustering over Attributed Graphs

    Zheng, H., Yang, R. & Xu, J., 20 May 2025, Proceedings of the 41st IEEE International Conference on Data Engineering, ICDE 2025. Hong Kong: IEEE, p. 2052-2065 14 p. (International Conference on Data Engineering).

    Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

  • Diffusion-based Graph-agnostic Clustering

    Xie, K., YANG, R. & Wang, S., 22 Apr 2025, Proceedings of the ACM on Web Conference 2025. New York: Association for Computing Machinery (ACM), p. 1353-1364 12 p. (Proceedings of the ACM on Web Conference 2025).

    Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

    Open Access
  • Empowering Graph-based Approximate Nearest Neighbor Search with Adaptive Awareness Capabilities

    Ruan, J., Chen, T., Yang, R., Ke, X. & Gao, Y., 3 Aug 2025, KDD '25: Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery (ACM), 11 p. (KDD: Proceedings of ACM SIGKDD Conference on Knowledge Discovery and Data Mining).

    Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

  • Grasp: Simple yet effective graph similarity predictions

    ZHENG, H., Shi, J. & YANG, R., 11 Apr 2025, Proceedings of the AAAI Conference on Artificial Intelligence. Walsh, T., Shah, J. & Kolter, Z. (eds.). 21 ed. New York: AAAI Conference on Artificial Intelligence, Vol. 39. p. 22884-22892 9 p. (Proceedings of the AAAI Conference on Artificial Intelligence; vol. 39, no. 21).

    Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

  • Leveraging Large Language Models for Effective Label-free Node Classification in Text-Attributed Graphs

    Zhang, T., Yang, R., Lai, Y., Yan, M., Ye, X. & Fan, D., 13 Jul 2025, Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2025. Association for Computing Machinery (ACM), (Proceedings of the International ACM SIGIR Conference on Research and Development in Information Retrieval).

    Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review