Shijing Ma

1.1k citations
34 papers · 860 · h-index 18

Impact in

Papers in

Shijing Ma

31 papers receiving 846 citations

Peers

Shijing Ma
Comparison fields: 5 of 115
  • Biomaterials 108
  • Industrial and Manufacturing Engineering 79
  • Molecular Medicine 30
  • Materials Chemistry 273
  • Immunology 98
Replace Xinhai Zhu with:
Xinhai Zhu China
Ruinan Wang China
Congyan Liu China
Wenkuan Wang China
Yasuhiro Iida Japan
Sau L. Lee United States
Anna Niarakis France
Yinling Wang China
Yongfang Yao China
Xujun Zhang China
Shijing Ma relative to Xinhai Zhu China Xinhai Zhu's profile →
Citations per field
00.5×2.9×
Xinhai Zhu · 1×
Citations per year

Countries citing papers authored by Shijing Ma

Since Specialization
Citations

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

Fields of papers citing papers by Shijing Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016142
2 2016107
3 201767
4 201953
5 201450
6 201841
7 202038
8 201932
9 201731
10 201828
11 201628
12 201924
13 201922
14 202221
15 202021
16 201621
17 201819
18 201818
19 202014
20 202114

About Shijing Ma

Shijing Ma is a scholar working on Molecular Biology, Biomedical Engineering, Artificial Intelligence, Materials Chemistry and Computational Theory and Mathematics, having authored 34 papers that have together received 860 indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (6 papers), Nanoplatforms for cancer theranostics (4 papers), Graphene and Nanomaterials Applications (4 papers), Advanced Multi-Objective Optimization Algorithms (4 papers), Nanoparticle-Based Drug Delivery (3 papers), RNA modifications and cancer (3 papers), Advanced Manufacturing and Logistics Optimization (2 papers) and Scheduling and Optimization Algorithms (2 papers). The work is most often cited by research in Biomaterials (108 citations), Industrial and Manufacturing Engineering (79 citations), Molecular Medicine (30 citations), Materials Chemistry (273 citations) and Immunology (98 citations). Shijing Ma has collaborated with scholars based in China, United States and Thailand. Frequent co-authors include Xiangtao Li, Xi Zheng, Zhiyun Du, Yan He, Kun Zhang, Sen Jiang, Yue Liu, Shupeng Cheng, Dongli Li and Huarong Huang. Their work appears in journals such as International Journal of Biological Sciences, IEEE Access, Frontiers in Oncology, International Journal of Nanomedicine and Journal of Cancer.

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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