Peng Pan

40 total papers · 609 total citations
23 papers, 388 citations indexed

About

Peng Pan is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Peng Pan has authored 23 papers receiving a total of 388 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 9 papers in Information Systems and 5 papers in Computer Vision and Pattern Recognition. Recurrent topics in Peng Pan's work include Recommender Systems and Techniques (7 papers), Manufacturing Process and Optimization (4 papers) and Advanced Graph Neural Networks (4 papers). Peng Pan is often cited by papers focused on Recommender Systems and Techniques (7 papers), Manufacturing Process and Optimization (4 papers) and Advanced Graph Neural Networks (4 papers). Peng Pan collaborates with scholars based in China, United Kingdom and Macao. Peng Pan's co-authors include David K. Harrison, Guohui Li, Jianjun Li, Kai Cheng, Meng Liu, Chaoyang Wang, Jianjun Li, Ke Liu, Shuqin Wang and Qing Sun and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Information Sciences.

In The Last Decade

Peng Pan

20 papers receiving 365 citations

Author Peers

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

Author						Papers	Cites
Peng Pan	142	141	98	75	71	23	388
Ye Chen	137 1.0×	149 1.1×	59 0.6×	17 0.2×	87 1.2×	27	442
Chen‐Fang Tsai	49 0.3×	116 0.8×	66 0.7×	14 0.2×	84 1.2×	40	374
Julita Bermejo–Alonso	140 1.0×	60 0.4×	84 0.9×	77 1.0×	39 0.5×	27	373
C.C. Hayes	80 0.6×	21 0.1×	132 1.3×	66 0.9×	43 0.6×	34	365
Manas Bajaj	57 0.4×	53 0.4×	148 1.5×	60 0.8×	75 1.1×	21	359
Joshua Lubell	49 0.3×	68 0.5×	221 2.3×	43 0.6×	16 0.2×	36	374
Rajaram Ganeshan	178 1.3×	43 0.3×	45 0.5×	32 0.4×	22 0.3×	32	356
Jad El‐khoury	88 0.6×	92 0.7×	173 1.8×	52 0.7×	38 0.5×	45	436
Ye Hu	87 0.6×	182 1.3×	145 1.5×	53 0.7×	10 0.1×	27	444
Ahsan Qamar	111 0.8×	78 0.6×	192 2.0×	110 1.5×	48 0.7×	34	443

Countries citing papers authored by Peng Pan

Since Specialization

Citations

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

Fields of papers citing papers by Peng Pan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peng Pan

This figure shows the co-authorship network connecting the top 25 collaborators of Peng Pan. A scholar is included among the top collaborators of Peng Pan 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 Peng Pan. Peng Pan 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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