Zhu Sun

2.2k total citations · 1 hit paper
79 papers, 1.3k citations indexed

About

Zhu Sun is a scholar working on Information Systems, Artificial Intelligence and Management Science and Operations Research. According to data from OpenAlex, Zhu Sun has authored 79 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 53 papers in Information Systems, 41 papers in Artificial Intelligence and 16 papers in Management Science and Operations Research. Recurrent topics in Zhu Sun's work include Recommender Systems and Techniques (52 papers), Advanced Graph Neural Networks (20 papers) and Topic Modeling (17 papers). Zhu Sun is often cited by papers focused on Recommender Systems and Techniques (52 papers), Advanced Graph Neural Networks (20 papers) and Topic Modeling (17 papers). Zhu Sun collaborates with scholars based in Singapore, China and Australia. Zhu Sun's co-authors include Jie Zhang, Jie Yang, Alessandro Bozzon, Chi Xu, Guibing Guo, Long-Kai Huang, Shun‐Shi Zhong, Xinghua Qu, Qing Guo and Neil Yorke‐Smith and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Information Sciences and IEEE Transactions on Antennas and Propagation.

In The Last Decade

Zhu Sun

72 papers receiving 1.3k citations

Hit Papers

Recurrent knowledge graph embedding for effective recomme... 2018 2026 2020 2023 2018 50 100 150 200
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Recurrent knowledge graph embedding for effective recommendation
    2018 245 citations Zhu Sun, Jie Yang et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Zhu Sun Singapore 17 836 640 260 206 186 79 1.3k
Linke Guo United States 21 442 0.5× 894 1.4× 30 0.1× 220 1.1× 161 0.9× 81 1.5k
Zengbin Zhang United States 16 229 0.3× 163 0.3× 111 0.4× 783 3.8× 86 0.5× 33 1.3k
Mingjun Xiao China 19 198 0.2× 263 0.4× 45 0.2× 204 1.0× 163 0.9× 66 1.2k
Xin Xin China 19 625 0.7× 593 0.9× 13 0.1× 110 0.5× 169 0.9× 82 1.0k
Chuanhe Huang China 18 228 0.3× 296 0.5× 108 0.4× 374 1.8× 83 0.4× 124 1.1k
Ping Lü China 16 173 0.2× 294 0.5× 52 0.2× 77 0.4× 174 0.9× 63 715
Suguo Du China 16 195 0.2× 505 0.8× 114 0.4× 348 1.7× 60 0.3× 34 1.1k

Countries citing papers authored by Zhu Sun

Since Specialization
Citations

This map shows the geographic impact of Zhu Sun's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Zhu Sun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zhu Sun more than expected).

Fields of papers citing papers by Zhu Sun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Zhu Sun. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Zhu Sun. The network helps show where Zhu Sun may publish in the future.

Co-authorship network of co-authors of Zhu Sun

This figure shows the co-authorship network connecting the top 25 collaborators of Zhu Sun. A scholar is included among the top collaborators of Zhu Sun based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Zhu Sun. Zhu Sun is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Yang, Qinglin, Huawei Huang, Xuan Zhu, et al.. (2025). CrossMeta: A Fast and Cheap Cross-Metaverse Interoperability Protocol. IEEE Transactions on Services Computing. 1–14. 1 indexed citations
2.
Sun, Zhu, et al.. (2025). Model-Agnostic Social Network Refinement with Diffusion Models for Robust Social Recommendation. DR-NTU (Nanyang Technological University). 370–378.
3.
Liu, Jiao, et al.. (2025). Language Model Evolutionary Algorithms for Recommender Systems: Benchmarks and Algorithm Comparisons. IEEE Transactions on Evolutionary Computation. 1–1.
4.
Sun, Zhu, et al.. (2025). Enhancing New-item Fairness in Dynamic Recommender Systems. DR-NTU (Nanyang Technological University). 1707–1716. 1 indexed citations
5.
Li, Fan, et al.. (2025). A New Era in Human Factors Engineering: A Survey of the Applications and Prospects of Large Multimodal Models. International Journal of Human-Computer Interaction. 41(18). 11867–11880. 2 indexed citations
6.
Sun, Zhu, et al.. (2024). Unified Denoising Training for Recommendation. 612–621.
7.
Qu, Xinghua, et al.. (2024). Breaking the Silence: Whisper-Driven Emotion Recognition in AI Mental Support Models. 290–291. 1 indexed citations
8.
Sun, Zhu, et al.. (2024). Large Language Models for Intent-Driven Session Recommendations. 324–334. 13 indexed citations
9.
10.
Sun, Zhu, Jie Yang, Xinghua Qu, et al.. (2024). Adaptive In-Context Learning with Large Language Models for Bundle Generation. 966–976. 2 indexed citations
11.
Yang, Xiaochun, et al.. (2024). Adaptive Intention Learning for Session-Based Recommendation. ACM Transactions on Intelligent Systems and Technology. 16(2). 1–26. 1 indexed citations
12.
Sun, Zhu, et al.. (2024). Configurable Fairness for New Item Recommendation Considering Entry Time of Items. 437–447. 2 indexed citations
13.
Zhang, Danning, et al.. (2023). Purpose tendency-aware diversified strategy for effective session-based recommendation. Electronic Commerce Research and Applications. 57. 101235–101235. 3 indexed citations
14.
Fang, Hui, et al.. (2023). Understanding Diversity in Session-based Recommendation. ACM Transactions on Information Systems. 42(1). 1–34. 7 indexed citations
15.
Sun, Zhu, et al.. (2023). A Multi-channel Next POI Recommendation Framework with Multi-granularity Check-in Signals. ACM Transactions on Information Systems. 42(1). 1–28. 7 indexed citations
16.
17.
Qu, Xinghua, et al.. (2023). Towards Building Voice-based Conversational Recommender Systems: Datasets, Potential Solutions and Prospects. arXiv (Cornell University). 2701–2711. 4 indexed citations
18.
Sun, Zhu, Hui Fang, Jie Yang, et al.. (2022). DaisyRec 2.0: Benchmarking Recommendation for Rigorous Evaluation. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(7). 8206–8226. 12 indexed citations
19.
Sun, Zhu, et al.. (2022). Who Wants to Shop With You: Joint Product–Participant Recommendation for Group-Buying Service. IEEE Transactions on Neural Networks and Learning Systems. 35(2). 2353–2363. 2 indexed citations
20.
Qu, Xinghua, Zhu Sun, Yew-Soon Ong, Abhishek Gupta, & Pengfei Wei. (2020). Minimalistic Attacks: How Little It Takes to Fool Deep Reinforcement Learning Policies. IEEE Transactions on Cognitive and Developmental Systems. 13(4). 806–817. 19 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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