Renjun Hu

401 total citations
18 papers, 248 citations indexed

About

Renjun Hu is a scholar working on Information Systems, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Renjun Hu has authored 18 papers receiving a total of 248 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Information Systems, 8 papers in Artificial Intelligence and 6 papers in Signal Processing. Recurrent topics in Renjun Hu's work include Recommender Systems and Techniques (6 papers), Data Management and Algorithms (6 papers) and Complex Network Analysis Techniques (5 papers). Renjun Hu is often cited by papers focused on Recommender Systems and Techniques (6 papers), Data Management and Algorithms (6 papers) and Complex Network Analysis Techniques (5 papers). Renjun Hu collaborates with scholars based in China, United States and Netherlands. Renjun Hu's co-authors include Shuai Ma, Jinpeng Huai, Hui Xiong, Charų C. Aggarwal, Hao Liu, Xuelian Lin, Yanjie Fu, Jingjing Gu, Ting Li and Jingbo Zhou and has published in prestigious journals such as IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Multimedia and IEEE Transactions on Mobile Computing.

In The Last Decade

Renjun Hu

17 papers receiving 245 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Renjun Hu China	8	125	73	68	60	59	18	248
Paolo Rosso Switzerland	7	182 1.5×	95 1.3×	87 1.3×	23 0.4×	42 0.7×	16	292
Shuai Xu China	7	62 0.5×	86 1.2×	64 0.9×	42 0.7×	49 0.8×	34	211
Kaiyu Feng Singapore	11	90 0.7×	49 0.7×	57 0.8×	75 1.3×	60 1.0×	21	266
Tim Hanratty United States	6	116 0.9×	214 2.9×	70 1.0×	35 0.6×	68 1.2×	10	363
Yaqiong Qiao China	9	140 1.1×	46 0.6×	69 1.0×	31 0.5×	35 0.6×	33	246
Haoruo Peng United States	12	386 3.1×	61 0.8×	49 0.7×	20 0.3×	22 0.4×	21	471
Yile Liang China	7	185 1.5×	148 2.0×	299 4.4×	36 0.6×	9 0.2×	10	393
Guolei Yang United States	7	127 1.0×	35 0.5×	60 0.9×	26 0.4×	7 0.1×	12	189
Ionut Trestian United States	8	104 0.8×	68 0.9×	55 0.8×	222 3.7×	21 0.4×	10	296
Jarana Manotumruksa United Kingdom	8	175 1.4×	120 1.6×	201 3.0×	33 0.6×	7 0.1×	18	323

Countries citing papers authored by Renjun Hu

Since Specialization

Citations

This map shows the geographic impact of Renjun Hu'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 Renjun Hu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Renjun Hu more than expected).

Fields of papers citing papers by Renjun Hu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Renjun Hu. 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 Renjun Hu. The network helps show where Renjun Hu may publish in the future.

Co-authorship network of co-authors of Renjun Hu

This figure shows the co-authorship network connecting the top 25 collaborators of Renjun Hu. A scholar is included among the top collaborators of Renjun Hu 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 Renjun Hu. Renjun Hu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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18 of 18 papers shown

Cheng, Yi, et al.. (2024). Arithmetic Feature Interaction Is Necessary for Deep Tabular Learning. Proceedings of the AAAI Conference on Artificial Intelligence. 38(10). 11516–11524. 3 indexed citations

Ying, Haochao, et al.. (2024). A Progressively-Passing-Then-Disentangling Approach to Recipe Recommendation. IEEE Transactions on Multimedia. 27. 2760–2771.

Ying, Haochao, et al.. (2023). Robust Image Ordinal Regression with Controllable Image Generation. 627–635. 1 indexed citations

Ying, Haochao, Renjun Hu, Jingbo Zhou, et al.. (2023). Robust Training of Graph Neural Networks via Noise Governance. 607–615. 14 indexed citations

Yuan, Zixuan, Hao Liu, Junming Liu, et al.. (2021). Incremental Spatio-Temporal Graph Learning for Online Query-POI Matching. CityU Scholars. 1586–1597. 8 indexed citations

Yuan, Zixuan, Hao Liu, Renjun Hu, Denghui Zhang, & Hui Xiong. (2021). Self-Supervised Prototype Representation Learning for Event-Based Corporate Profiling. Proceedings of the AAAI Conference on Artificial Intelligence. 35(5). 4644–4652. 7 indexed citations

Zhou, Jingbo, Tao Huang, Shuangli Li, et al.. (2021). Competitive Relationship Prediction for Points of Interest: A Neural Graphlet Based Approach. IEEE Transactions on Knowledge and Data Engineering. 34(12). 5681–5692. 7 indexed citations

Ma, Shuai, et al.. (2020). Athena. 841–844. 1 indexed citations

Hu, Renjun, Xinjiang Lu, Chuanren Liu, et al.. (2020). Why We Go Where We Go: Profiling User Decisions on Choosing POIs. 3459–3465. 3 indexed citations

10.

Hu, Renjun, et al.. (2020). Exploiting User Preference and Mobile Peer Influence for Human Mobility Annotation. ACM Transactions on Knowledge Discovery from Data. 14(6). 1–18. 3 indexed citations

11.

Hu, Renjun, Jingbo Zhou, Xinjiang Lu, et al.. (2020). NCF: A Neural Context Fusion Approach to Raw Mobility Annotation. IEEE Transactions on Mobile Computing. 1–1. 7 indexed citations

12.

Liu, Hao, Ting Li, Renjun Hu, et al.. (2019). Joint Representation Learning for Multi-Modal Transportation Recommendation. Proceedings of the AAAI Conference on Artificial Intelligence. 33(1). 1036–1043. 56 indexed citations

13.

Ma, Shuai, et al.. (2019). An Efficient Approach to Finding Dense Temporal Subgraphs. IEEE Transactions on Knowledge and Data Engineering. 32(4). 645–658. 11 indexed citations

14.

Zhou, Jingbo, Renjun Hu, Dongxiang Zhang, et al.. (2019). A Collaborative Learning Framework to Tag Refinement for Points of Interest. 1752–1761. 25 indexed citations

15.

Ma, Shuai, et al.. (2018). Query Independent Scholarly Article Ranking. 953–964. 5 indexed citations

16.

Ma, Shuai, et al.. (2017). Fast Computation of Dense Temporal Subgraphs. 361–372. 43 indexed citations

17.

Hu, Renjun, Charų C. Aggarwal, Shuai Ma, & Jinpeng Huai. (2016). An embedding approach to anomaly detection. 385–396. 41 indexed citations

18.

Aggarwal, Charų C., et al.. (2016). Scaling up Link Prediction with Ensembles. 367–376. 13 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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