Jiahao Li

528 total citations
30 papers, 179 citations indexed

About

Jiahao Li is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Mechanical Engineering. According to data from OpenAlex, Jiahao Li has authored 30 papers receiving a total of 179 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Artificial Intelligence, 7 papers in Computer Vision and Pattern Recognition and 4 papers in Mechanical Engineering. Recurrent topics in Jiahao Li's work include Natural Language Processing Techniques (4 papers), Topic Modeling (3 papers) and Data Quality and Management (3 papers). Jiahao Li is often cited by papers focused on Natural Language Processing Techniques (4 papers), Topic Modeling (3 papers) and Data Quality and Management (3 papers). Jiahao Li collaborates with scholars based in China, United Kingdom and United States. Jiahao Li's co-authors include Shutao Li, Xudong Kang, Bin Sun, Mohammed Bennamoun, Xiaoyuan Lu, Qiguang Miao, Guangming Zhu, Liang Zhang, Guoqing Lu and Syed Afaq Ali Shah and has published in prestigious journals such as IEEE Transactions on Geoscience and Remote Sensing, International Journal for Numerical Methods in Engineering and Applied Thermal Engineering.

In The Last Decade

Jiahao Li

18 papers receiving 173 citations

Peers

Jiahao Li
Comparison fields: 5 of 50
  • Artificial Intelligence 95
  • Computer Vision and Pattern Recognition 68
  • Control and Systems Engineering 27
  • Media Technology 27
  • Electrical and Electronic Engineering 16
Replace Lingyan Ran with:
Lingyan Ran China
Ruoxi Deng China
Görkem Algan Türkiye
Hao Kang United States
Hezheng Lin China
Kunchang Li Singapore
Yuanwei Wu United States
Zunaira Rauf Pakistan
James Gabriel United States
Lingyan Ran China View profile →
Citations per field, relative to Jiahao Li
Jiahao Li · 1×
Citations per year, relative to Jiahao Li
Jiahao Li · 1×

Countries citing papers authored by Jiahao Li

Since Specialization
Citations

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

Fields of papers citing papers by Jiahao Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jiahao Li

This figure shows the co-authorship network connecting the top 25 collaborators of Jiahao Li. A scholar is included among the top collaborators of Jiahao Li 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 Jiahao Li. Jiahao Li 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 0
2 1
3 0
4 0
5 0
6 3
7 0
8 5
9 0
10 0
11 4
12 1
13 0
14 2
15 1
16 9
17 0
18 2
19 40
20 1

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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