Mark Junjie Li

1.2k citations
26 papers · 612 · h-index 11

Impact in

Papers in

Mark Junjie Li

24 papers receiving 594 citations

Peers

Mark Junjie Li
Comparison fields: 5 of 113
  • Artificial Intelligence 302
  • Signal Processing 89
  • Computer Vision and Pattern Recognition 148
  • Sensory Systems 26
  • Information Systems 79
Replace Tong Zhao with:
Tong Zhao China
Tongfeng Sun China
Xu Yang China
Shujian Yu China
Muhammad Iqbal New Zealand
Liang Xie China
Yugen Yi China
Giovanni Motta United States
Naveen Kumar India
Yin-Wen Chang United States
Mark Junjie Li relative to Tong Zhao China Tong Zhao's profile →
Citations per field
00.5×4.3×
Tong Zhao · 1×
Citations per year

Countries citing papers authored by Mark Junjie Li

Since Specialization
Citations

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

Fields of papers citing papers by Mark Junjie Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Mark Junjie 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 Mark Junjie Li Line = papers co-authored together Mark Junjie Li links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008207
2 2007147
3 201576
4 202030
5 201525
6 201820
7 201020
8 201819
9 202414
10 202112
11 201910
12 20148
13 20096
14 20064
15 20193
16 20243
17 20241
18 20231
19 20251
20 20191

About Mark Junjie Li

Mark Junjie Li is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology, Information Systems and Control and Systems Engineering, having authored 26 papers that have together received 612 indexed citations. Recurring topics across this work include Advanced Clustering Algorithms Research (5 papers), Gene expression and cancer classification (3 papers), Face and Expression Recognition (3 papers), Anomaly Detection Techniques and Applications (3 papers), Data Mining Algorithms and Applications (2 papers), Algorithms and Data Compression (2 papers), Energy Load and Power Forecasting (2 papers) and Hydrological Forecasting Using AI (2 papers). The work is most often cited by research in Artificial Intelligence (302 citations), Signal Processing (89 citations), Computer Vision and Pattern Recognition (148 citations), Sensory Systems (26 citations) and Information Systems (79 citations). Mark Junjie Li has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Michael K. Ng, Joshua Zhexue Huang, Yiu‐ming Cheung, Jian Huang, Zengyou He, Qingyao Wu, Thanh-Tung Nguyen, Nguyễn Thị Thanh Thủy, Thanh-Tung Nguyen and Yunming Ye. Their work appears in journals such as Journal of Biomedical Informatics, Neurocomputing, IEEE Transactions on Multimedia, Ageing Research Reviews and BMC Genomics.

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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