Tian Han

1.2k total citations · 1 hit paper
48 papers, 704 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 704 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 Solar Radiation and Photovoltaics (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 Solar Radiation and Photovoltaics (3 papers). Tian Han collaborates with scholars based in China, United States and Hong Kong. Tian Han's co-authors include Bo‐Suk Yang, Yongsu Kim, Jia Cheng, Fei Zhu, Zhong Lin Wang, Yijia Lu, Bin Liu, Linhong Ji, Song‐Chun Zhu and Yang Lu 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 675 citations

Hit Papers

Decoding lip language using triboelectric sensors with de... 2022 2026 2023 2024 2022 50 100 150

Peers

Tian Han
Comparison fields: 5 of 124
  • Biomedical Engineering 180
  • Artificial Intelligence 164
  • Control and Systems Engineering 98
  • Computer Vision and Pattern Recognition 91
  • Cognitive Neuroscience 90
Tao Hou China
Jin Xu China
Chengwei Huang China
Yu Xie China
Lei Yu China
Yubin Liu China
Yu Du China
Guobin Chen China
Junhao Zhao China
Tao Hou China View profile →
Citations per field, relative to Tian Han
Tian Han · 1×
Citations per year, relative to Tian Han
Tian Han · 1×

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

20 of 20 papers shown
# Work Indexed citations
1 1
2 5
3 0
4
Improving Adversarial Energy-Based Model via Diffusion Process
0
5 1
6 6
7 0
8 15
9 1
10 1
11 1
12 1
13 7
14 17
15 5
16
Decoding lip language using triboelectric sensors with deep learning breakdown →
193
17 4
18 22
19 1
20 3

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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