Jiaqi Wang

1.8k total citations · 1 hit paper
86 papers, 1.4k citations indexed

About

Jiaqi Wang is a scholar working on Materials Chemistry, Electrical and Electronic Engineering and Molecular Biology. According to data from OpenAlex, Jiaqi Wang has authored 86 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Materials Chemistry, 22 papers in Electrical and Electronic Engineering and 12 papers in Molecular Biology. Recurrent topics in Jiaqi Wang's work include Ferroelectric and Piezoelectric Materials (6 papers), Supramolecular Self-Assembly in Materials (6 papers) and Machine Learning in Materials Science (5 papers). Jiaqi Wang is often cited by papers focused on Ferroelectric and Piezoelectric Materials (6 papers), Supramolecular Self-Assembly in Materials (6 papers) and Machine Learning in Materials Science (5 papers). Jiaqi Wang collaborates with scholars based in China, United States and Japan. Jiaqi Wang's co-authors include Seungha Shin, Anming Hu, Zhang Zhi, Linfang Zhang, Guokai Fu, Xiangxue Wang, Xing Li, Xing‐Jie Liang, Juyoung Yoon and Jing Zhao and has published in prestigious journals such as Journal of the American Chemical Society, Advanced Materials and Nature Communications.

In The Last Decade

Jiaqi Wang

72 papers receiving 1.3k citations

Hit Papers

BODIPY as a Multifunctional Theranostic Reagent in Biomed... 2022 2026 2023 2024 2022 50 100 150

Peers

Jiaqi Wang
Comparison fields: 5 of 119
  • Materials Chemistry 648
  • Electrical and Electronic Engineering 311
  • Biomedical Engineering 268
  • Mechanical Engineering 163
  • Inorganic Chemistry 132
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Xiaoqian Xu China View profile →
Citations per field, relative to Jiaqi Wang
Jiaqi Wang · 1×
Citations per year, relative to Jiaqi Wang
Jiaqi Wang · 1×

Countries citing papers authored by Jiaqi Wang

Since Specialization
Citations

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

Fields of papers citing papers by Jiaqi Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jiaqi Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Jiaqi Wang. A scholar is included among the top collaborators of Jiaqi Wang 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 Jiaqi Wang. Jiaqi Wang 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 0
3 3
4 3
5 0
6 4
7 2
8 9
9 9
10 3
11 1
12 33
13 0
14 25
15 32
16 18
17 25
18 3
19
The Model of Relative Reinforcement Learning Using Multi-ant Cooperation Based on Regret Values
1
20
Word Document Automatically Generated Technology Based on VC
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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