Yue Cui

484 total citations
26 papers, 300 citations indexed

About

Yue Cui is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Building and Construction. According to data from OpenAlex, Yue Cui has authored 26 papers receiving a total of 300 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 6 papers in Computer Vision and Pattern Recognition and 6 papers in Building and Construction. Recurrent topics in Yue Cui's work include Traffic Prediction and Management Techniques (6 papers), Transportation Planning and Optimization (3 papers) and Time Series Analysis and Forecasting (3 papers). Yue Cui is often cited by papers focused on Traffic Prediction and Management Techniques (6 papers), Transportation Planning and Optimization (3 papers) and Time Series Analysis and Forecasting (3 papers). Yue Cui collaborates with scholars based in China, Hong Kong and Denmark. Yue Cui's co-authors include Yan Zhao, Xiaofang Zhou, Kai Zheng, Kai Zheng, Kai Zheng, Liwei Deng, Feida Zhu, Han Su, Hao Sun and Hongzhi Yin and has published in prestigious journals such as Monthly Notices of the Royal Astronomical Society, IEEE Transactions on Knowledge and Data Engineering and Frontiers in Pharmacology.

In The Last Decade

Yue Cui

23 papers receiving 292 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Yue Cui China	8	86	80	76	70	63	26	300
Saurabh Nangia United States	5	102 1.2×	104 1.3×	134 1.8×	41 0.6×	16 0.3×	8	351
Nirnay Ghosh India	10	123 1.4×	74 0.9×	180 2.4×	11 0.2×	26 0.4×	31	352
Songnian Zhang Canada	13	328 3.8×	21 0.3×	53 0.7×	6 0.1×	107 1.7×	69	529
Georgios Kellaris United States	6	372 4.3×	47 0.6×	81 1.1×	23 0.3×	76 1.2×	7	447
Abdallah M’Hamed France	6	68 0.8×	118 1.5×	155 2.0×	18 0.3×	16 0.3×	12	274
Madhuri Siddula United States	11	152 1.8×	13 0.2×	19 0.3×	14 0.2×	32 0.5×	23	329
Daichi Amagata Japan	12	163 1.9×	36 0.5×	14 0.2×	8 0.1×	160 2.5×	55	372
Ferdinando Fioretto United States	12	220 2.6×	9 0.1×	21 0.3×	15 0.2×	76 1.2×	49	484
Yong-Feng Ge China	10	230 2.7×	8 0.1×	36 0.5×	20 0.3×	17 0.3×	29	338
Y. T. Chris United States	12	155 1.8×	32 0.4×	43 0.6×	5 0.1×	18 0.3×	40	558

Countries citing papers authored by Yue Cui

Since Specialization

Citations

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

Fields of papers citing papers by Yue Cui

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yue Cui

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Li, Shuhao, et al.. (2025). Unifying Lane-Level Traffic Prediction From a Graph Structural Perspective: Benchmark and Baseline. IEEE Transactions on Knowledge and Data Engineering. 37(9). 5699–5718.

Li, Shuhao, et al.. (2024). ST-ABC: Spatio-Temporal Attention-Based Convolutional Network for Multi-Scale Lane-Level Traffic Prediction. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 1185–1198. 5 indexed citations

Ye, Qingqing, et al.. (2024). FRESH: Towards Efficient Graph Queries in an Outsourced Graph. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 4545–4557. 1 indexed citations

Cui, Yue, et al.. (2024). Correction to: Recovering the wedge modes lost to 21-cm foregrounds. Monthly Notices of the Royal Astronomical Society. 529(3). 2539–2542. 1 indexed citations

Kennedy, Jacob J., et al.. (2024). Machine-learning recovery of foreground wedge-removed 21-cm light cones for high-z galaxy mapping. Monthly Notices of the Royal Astronomical Society. 529(4). 3684–3698. 9 indexed citations

Zhang, Rui-Xin, Yue Cui, Hongyang Wang, Dan Qin, & Jing Li. (2024). In silico characterization of Rhodotorula toruloides ELO-like elongases and production of very-long-chain fatty acids by expressing Rtelo2, RtKCR, RtHCD, and RtECR through IRES-mediated bicistrons. World Journal of Microbiology and Biotechnology. 40(12). 395–395. 1 indexed citations

Li, Shuhao, et al.. (2024). Seeing the Forest for the Trees: Road-Level Insights Assisted Lane-Level Traffic Prediction. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 1266–1275. 1 indexed citations

Li, Shuhao, et al.. (2023). ST-MoE: Spatio-Temporal Mixture-of-Experts for Debiasing in Traffic Prediction. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 1208–1217. 6 indexed citations

Cui, Yue, Qingqing Ye, Yan Zhao, et al.. (2023). TED+: Towards Discovering Top-k Edge-Diversified Patterns in a Graph Database. IEEE Transactions on Knowledge and Data Engineering. 36(5). 2224–2238. 1 indexed citations

10.

Huang, Kai, et al.. (2023). VisualNeo: Bridging the Gap between Visual Query Interfaces and Graph Query Engines. Proceedings of the VLDB Endowment. 16(12). 4010–4013. 2 indexed citations

11.

Cui, Yue, Chen Ma, Kai Zheng, Lei Chen, & Xiaofang Zhou. (2023). Controllable Universal Fair Representation Learning. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 949–959. 3 indexed citations

12.

Li, Linjie, et al.. (2022). Cross-Adversarial Learning for Molecular Generation in Drug Design. Frontiers in Pharmacology. 12. 827606–827606. 7 indexed citations

13.

Cui, Yue, et al.. (2022). MARINA. Proceedings of the 31st ACM International Conference on Information & Knowledge Management. 2230–2239. 5 indexed citations

14.

Cui, Yue, Hao Sun, Yan Zhao, Hongzhi Yin, & Kai Zheng. (2021). Sequential-Knowledge-Aware Next POI Recommendation: A Meta-Learning Approach. ACM Transactions on Information Systems. 40(2). 1–22. 45 indexed citations

15.

Cui, Yue, et al.. (2021). METRO. Proceedings of the VLDB Endowment. 15(2). 224–236. 41 indexed citations

16.

Cui, Yue, et al.. (2021). Historical Inertia. 2965–2969. 38 indexed citations

17.

Cui, Yue, Liwei Deng, Yan Zhao, et al.. (2019). Hidden POI Ranking with Spatial Crowdsourcing. 814–824. 30 indexed citations

18.

Chen, Zhi‐Gang, et al.. (2012). Segmentation of Complex Microscopic Cell Image Based on Contourlet and Level Set. Advanced materials research. 429. 298–302. 1 indexed citations

19.

Cui, Yue, et al.. (2011). Research and Progress of Image Compression Coding Based on Wavelet. Advanced materials research. 403-408. 1352–1355.

20.

Wang, Baoying, Fei Pan, Yue Cui, & William Perrizo. (2003). Efficient Quantitative Frequent Pattern Mining Using Predicate Trees.. 168–171. 1 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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