Shanshan Wan

64 total papers · 576 total citations
38 papers, 411 citations indexed

About

Shanshan Wan is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Shanshan Wan has authored 38 papers receiving a total of 411 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 11 papers in Information Systems and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Shanshan Wan's work include Recommender Systems and Techniques (7 papers), Advanced Graph Neural Networks (5 papers) and Infrastructure Maintenance and Monitoring (4 papers). Shanshan Wan is often cited by papers focused on Recommender Systems and Techniques (7 papers), Advanced Graph Neural Networks (5 papers) and Infrastructure Maintenance and Monitoring (4 papers). Shanshan Wan collaborates with scholars based in China, United States and Tanzania. Shanshan Wan's co-authors include Zhendong Niu, Pei‐Jung Chung, B. Mulgrew, Chuan Qin, Hao Lü, Kaize Shi, Qika Lin, Yifan Zhu, Xingyu Wang and Yunlong Zhang and has published in prestigious journals such as Scientific Reports, IEEE Access and Building and Environment.

In The Last Decade

Shanshan Wan

34 papers receiving 398 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Shanshan Wan	210	197	168	48	35	38	411
Andrew Kwok-Fai Lui	78 0.4×	162 0.8×	76 0.5×	50 1.0×	63 1.8×	43	405
Guillermo Licea	162 0.8×	161 0.8×	65 0.4×	33 0.7×	54 1.5×	44	451
T. V. Geetha	89 0.4×	149 0.8×	40 0.2×	17 0.4×	59 1.7×	38	387
Dorina Kabakchieva	136 0.6×	186 0.9×	259 1.5×	8 0.2×	14 0.4×	41	481
Ricardo Queirós	83 0.4×	65 0.3×	200 1.2×	116 2.4×	17 0.5×	57	391
Evelio J. González	50 0.2×	66 0.3×	99 0.6×	54 1.1×	30 0.9×	42	393
Leonard L. Tripp	345 1.6×	113 0.6×	73 0.4×	11 0.2×	7 0.2×	34	465
Sanjay Kumar Jain	231 1.1×	230 1.2×	26 0.2×	9 0.2×	54 1.5×	30	431
Arti Ramesh	44 0.2×	206 1.0×	179 1.1×	33 0.7×	23 0.7×	30	479
Nayer Wanas	146 0.7×	227 1.2×	24 0.1×	10 0.2×	63 1.8×	34	445

Countries citing papers authored by Shanshan Wan

Since Specialization

Citations

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

Fields of papers citing papers by Shanshan Wan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shanshan Wan

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

All Works

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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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