Wei Peng

162 total papers · 1.2k total citations
72 papers, 634 citations indexed

About

Wei Peng is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Materials Chemistry. According to data from OpenAlex, Wei Peng has authored 72 papers receiving a total of 634 indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Artificial Intelligence, 10 papers in Computer Vision and Pattern Recognition and 8 papers in Materials Chemistry. Recurrent topics in Wei Peng's work include Topic Modeling (30 papers), Natural Language Processing Techniques (21 papers) and Multimodal Machine Learning Applications (9 papers). Wei Peng is often cited by papers focused on Topic Modeling (30 papers), Natural Language Processing Techniques (21 papers) and Multimodal Machine Learning Applications (9 papers). Wei Peng collaborates with scholars based in China, United States and Germany. Wei Peng's co-authors include Anhad Mohananey, Alex Warstadt, Sheng‐Fu Wang, Haokun Liu, Samuel R. Bowman, Alicia Parrish, Wenzhou Yu, Weiyan Jiang, Jiangyan Wang and Yue Hu and has published in prestigious journals such as Angewandte Chemie International Edition, Advanced Energy Materials and Journal of Cleaner Production.

In The Last Decade

Wei Peng

66 papers receiving 620 citations

Author Peers

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

Author						Papers	Cites
Wei Peng	335	81	69	48	44	72	634
Yunhao Zhang	75 0.2×	77 1.0×	132 1.9×	84 1.8×	33 0.8×	75	756
An Yan	113 0.3×	77 1.0×	49 0.7×	37 0.8×	32 0.7×	61	714
Le Gao	137 0.4×	64 0.8×	43 0.6×	70 1.5×	5 0.1×	107	765
Shuji Yoshizawa	198 0.6×	104 1.3×	13 0.2×	31 0.6×	19 0.4×	70	792
Mei Wang	105 0.3×	44 0.5×	197 2.9×	19 0.4×	19 0.4×	67	636
Ke Zhang	141 0.4×	215 2.7×	112 1.6×	45 0.9×	3 0.1×	49	748
Huaiwen Zhang	225 0.7×	17 0.2×	122 1.8×	14 0.3×	55 1.3×	51	620
Chen Jiang	82 0.2×	50 0.6×	142 2.1×	32 0.7×	11 0.3×	56	628
Shuai Zhang	52 0.2×	27 0.3×	23 0.3×	42 0.9×	17 0.4×	51	588
Ye Zheng	104 0.3×	102 1.3×	48 0.7×	50 1.0×	52 1.2×	61	761

Countries citing papers authored by Wei Peng

Since Specialization

Citations

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

Fields of papers citing papers by Wei Peng

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wei Peng

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