Chang Wei Tan

154 total papers · 1.6k total citations
51 papers, 770 citations indexed

About

Chang Wei Tan is a scholar working on Signal Processing, Electrical and Electronic Engineering and Artificial Intelligence. According to data from OpenAlex, Chang Wei Tan has authored 51 papers receiving a total of 770 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Signal Processing, 9 papers in Electrical and Electronic Engineering and 7 papers in Artificial Intelligence. Recurrent topics in Chang Wei Tan's work include Time Series Analysis and Forecasting (16 papers), Music and Audio Processing (8 papers) and Complex Systems and Time Series Analysis (6 papers). Chang Wei Tan is often cited by papers focused on Time Series Analysis and Forecasting (16 papers), Music and Audio Processing (8 papers) and Complex Systems and Time Series Analysis (6 papers). Chang Wei Tan collaborates with scholars based in Australia, China and United States. Chang Wei Tan's co-authors include Geoffrey I. Webb, Christoph Bergmeir, Navid Mohammadi Foumani, Mahsa Salehi, François Petitjean, Enhong Chen, Hui Xiong, Qi Liu, Lynn Miller and Germain Forestier and has published in prestigious journals such as Journal of the American Chemical Society, SHILAP Revista de lepidopterología and Scientific Reports.

In The Last Decade

Chang Wei Tan

46 papers receiving 745 citations

Hit Papers

Deep Learning for Time Se... 2024 2026 2024 20 40 60

Author Peers

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

Author Last Decade Papers Cites
Chang Wei Tan 240 239 95 92 70 51 770
Xuchao Zhang 377 1.6× 201 0.8× 28 0.3× 31 0.3× 18 0.3× 53 652
Xiaofeng Zou 200 0.8× 57 0.2× 34 0.4× 108 1.2× 28 0.4× 67 885
Jun Li 243 1.0× 39 0.2× 39 0.4× 49 0.5× 40 0.6× 63 679
Xiaoye Jiang 274 1.1× 60 0.3× 69 0.7× 34 0.4× 150 2.1× 23 809
Xiaofei Wang 293 1.2× 65 0.3× 31 0.3× 67 0.7× 30 0.4× 63 801
Lu Jiang 209 0.9× 35 0.1× 101 1.1× 32 0.3× 104 1.5× 72 866
Hao Wang 380 1.6× 75 0.3× 17 0.2× 29 0.3× 41 0.6× 51 838
Hang Liu 150 0.6× 69 0.3× 50 0.5× 71 0.8× 30 0.4× 74 799
Qindong Sun 325 1.4× 103 0.4× 30 0.3× 59 0.6× 23 0.3× 79 883
Warren Koontz 295 1.2× 117 0.5× 44 0.5× 44 0.5× 26 0.4× 18 735

Countries citing papers authored by Chang Wei Tan

Since Specialization
Citations

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

Fields of papers citing papers by Chang Wei Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chang Wei Tan

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