Lap-Mou Tam

44 total papers · 1.1k total citations
35 papers, 815 citations indexed

About

Lap-Mou Tam is a scholar working on Statistical and Nonlinear Physics, Mechanical Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Lap-Mou Tam has authored 35 papers receiving a total of 815 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Statistical and Nonlinear Physics, 9 papers in Mechanical Engineering and 8 papers in Computer Vision and Pattern Recognition. Recurrent topics in Lap-Mou Tam's work include Chaos control and synchronization (17 papers), Chaos-based Image/Signal Encryption (8 papers) and Neural Networks and Applications (6 papers). Lap-Mou Tam is often cited by papers focused on Chaos control and synchronization (17 papers), Chaos-based Image/Signal Encryption (8 papers) and Neural Networks and Applications (6 papers). Lap-Mou Tam collaborates with scholars based in Macao, Taiwan and United States. Lap-Mou Tam's co-authors include Afshin J. Ghajar, Hsien-Keng Chen, Long-Jye Sheu, Juhn-Horng Chen, Wen‐Chin Chen, Shih-Yu Li, Qiuwang Wang, Ting Ma, Yitung Chen and Yingxiao Li and has published in prestigious journals such as Energy, Sensors and Information Sciences.

In The Last Decade

Lap-Mou Tam

33 papers receiving 772 citations

Author Peers

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

Author Last Decade Papers Cites
Lap-Mou Tam 345 301 229 188 153 35 815
Ming-Jyi Jang 255 0.7× 244 0.8× 62 0.3× 146 0.8× 281 1.8× 34 937
Arkadiusz Syta 386 1.1× 269 0.9× 47 0.2× 143 0.8× 86 0.6× 48 883
Tamás Kalmár‐Nagy 299 0.9× 194 0.6× 109 0.5× 227 1.2× 38 0.2× 66 908
Mohamed Adel 79 0.2× 201 0.7× 71 0.3× 85 0.5× 404 2.6× 98 773
M. Shamsi 101 0.3× 127 0.4× 149 0.7× 58 0.3× 451 2.9× 54 988
Chunbiao Gan 265 0.8× 219 0.7× 66 0.3× 127 0.7× 18 0.1× 50 711
Dongmei Huang 504 1.5× 99 0.3× 83 0.4× 196 1.0× 30 0.2× 75 941
Grzegorz Kudra 135 0.4× 233 0.8× 59 0.3× 107 0.6× 60 0.4× 71 714
Biaosong Chen 169 0.5× 51 0.2× 161 0.7× 76 0.4× 70 0.5× 52 996
Samir Bendoukha 82 0.2× 337 1.1× 39 0.2× 26 0.1× 168 1.1× 62 742

Countries citing papers authored by Lap-Mou Tam

Since Specialization
Citations

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

Fields of papers citing papers by Lap-Mou Tam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lap-Mou Tam. 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 Lap-Mou Tam. The network helps show where Lap-Mou Tam may publish in the future.

Co-authorship network of co-authors of Lap-Mou Tam

This figure shows the co-authorship network connecting the top 25 collaborators of Lap-Mou Tam. A scholar is included among the top collaborators of Lap-Mou Tam 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 Lap-Mou Tam. Lap-Mou Tam 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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