Jiaming Li

457 citations
33 papers · 339 · h-index 10

Impact in

Papers in

Jiaming Li

29 papers receiving 328 citations

Peers

Jiaming Li
Comparison fields: 5 of 47
  • Artificial Intelligence 114
  • Computer Vision and Pattern Recognition 77
  • Computer Networks and Communications 53
  • Energy Engineering and Power Technology 6
  • Industrial and Manufacturing Engineering 12
Replace Shivsubramani Krishnamoorthy with:
Shivsubramani Krishnamoorthy India
Xiaowen Zhang China
Abha Choubey India
Xianwei Li China
Mai Abdelhakim United States
Nuo Xu China
Muhammad Abdullah Tayyab Malaysia
Jianping Gao China
Jiaming Li relative to Shivsubramani Krishnamoorthy India Shivsubramani Krishnamoorthy's profile →
Citations per field
00.5×1.5×2×2.4×
Shivsubramani Krishnamoorthy · 1×
Citations per year

Countries citing papers authored by Jiaming Li

Since Specialization
Citations

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

Fields of papers citing papers by Jiaming Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jiaming Li, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jiaming Li Line = papers co-authored together Jiaming Li links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201889
2 201034
3 201528
4 202320
5 202118
6 201117
7 201917
8 202216
9 202416
10 202112
11 20079
12 20047
13 20247
14 20136
15 20236
16 20095
17 20155
18 20245
19 20194
20 20083

About Jiaming Li

Jiaming Li is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications, Experimental and Cognitive Psychology and Computer Graphics and Computer-Aided Design, having authored 33 papers that have together received 339 indexed citations. Recurring topics across this work include Peer-to-Peer Network Technologies (5 papers), Medical Image Segmentation Techniques (3 papers), Privacy-Preserving Technologies in Data (2 papers), Sentiment Analysis and Opinion Mining (2 papers), Emotion and Mood Recognition (2 papers), Advanced Neural Network Applications (2 papers), Solar Radiation and Photovoltaics (1 paper) and Ultrasound in Clinical Applications (1 paper). The work is most often cited by research in Artificial Intelligence (114 citations), Computer Vision and Pattern Recognition (77 citations), Computer Networks and Communications (53 citations), Energy Engineering and Power Technology (6 citations) and Industrial and Manufacturing Engineering (12 citations). Jiaming Li has collaborated with scholars based in China, Singapore and Australia. Frequent co-authors include Hoay Beng Gooi, Muhammad Qamar Raza, N. Mithulananthan, Kwang Y. Lee, Geoffrey C. James, Hsiao‐Hwa Chen, Wen‐Long Chin, Chai Kiat Yeo, Jian Jia and Jian Guang Zhao. Their work appears in journals such as Soil Dynamics and Earthquake Engineering, Optics Express, Software Practice and Experience, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Industrial Informatics.

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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