Tian Han

116 total papers · 1.2k total citations
48 papers, 689 citations indexed

About

Tian Han is a scholar working on Artificial Intelligence, Global and Planetary Change and Signal Processing. According to data from OpenAlex, Tian Han has authored 48 papers receiving a total of 689 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Artificial Intelligence, 8 papers in Global and Planetary Change and 6 papers in Signal Processing. Recurrent topics in Tian Han's work include Time Series Analysis and Forecasting (4 papers), Neural Networks and Applications (4 papers) and Stock Market Forecasting Methods (3 papers). Tian Han is often cited by papers focused on Time Series Analysis and Forecasting (4 papers), Neural Networks and Applications (4 papers) and Stock Market Forecasting Methods (3 papers). Tian Han collaborates with scholars based in China, Hong Kong and United States. Tian Han's co-authors include Yongsu Kim, Bo‐Suk Yang, Linhong Ji, Yijia Lu, Zhong Lin Wang, Bin Liu, Fei Zhu, Jia Cheng, Song‐Chun Zhu and Ying Wu and has published in prestigious journals such as Nature Communications, The Science of The Total Environment and Journal of Hydrology.

In The Last Decade

Tian Han

39 papers receiving 662 citations

Hit Papers

Decoding lip language usi... 2022 2026 2023 2024 2022 50 100 150

Author Peers

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

Author Last Decade Papers Cites
Tian Han 177 162 96 92 88 48 689
Tao Hou 216 1.2× 68 0.4× 50 0.5× 57 0.6× 80 0.9× 77 764
Yunfan Chen 84 0.5× 78 0.5× 56 0.6× 181 2.0× 27 0.3× 53 682
Il-Hwan Kim 124 0.7× 53 0.3× 70 0.7× 36 0.4× 23 0.3× 66 617
He Ren 82 0.5× 59 0.4× 46 0.5× 59 0.6× 18 0.2× 74 779
Hao Wang 164 0.9× 81 0.5× 34 0.4× 25 0.3× 39 0.4× 65 682
Hongyi Zhang 88 0.5× 54 0.3× 80 0.8× 67 0.7× 21 0.2× 50 596
Chengxi Li 135 0.8× 45 0.3× 52 0.5× 37 0.4× 17 0.2× 46 731
Jintao Liu 71 0.4× 84 0.5× 37 0.4× 72 0.8× 14 0.2× 63 766
Hui Li 118 0.7× 54 0.3× 81 0.8× 40 0.4× 8 0.1× 32 737
Salviano Soares 71 0.4× 78 0.5× 30 0.3× 83 0.9× 16 0.2× 77 722

Countries citing papers authored by Tian Han

Since Specialization
Citations

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

Fields of papers citing papers by Tian Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tian Han

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