Tong Wang

99 papers receiving 840 citations

Peers

Tong Wang
Comparison fields: 5 of 154
  • Mechanical Engineering 251
  • Artificial Intelligence 228
  • Materials Chemistry 107
  • Electrical and Electronic Engineering 79
  • Biomedical Engineering 73
Replace Sunil Gupta with:
Sunil Gupta Australia
Wenhao Zhu China
Stefano Di Carlo Italy
Qi Wu China
Dong Zhang China
Jinsu Kim South Korea
Yue He China
Manish Kumar Bajpai India
Pankaj Agarwal India
Abhishek Kumar India
Tong Wang relative to Sunil Gupta Australia Sunil Gupta's profile →
Citations per field
00.5×
Sunil Gupta · 1×
Citations per year

Countries citing papers authored by Tong Wang

Since Specialization
Citations

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

Fields of papers citing papers by Tong Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tong Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Tong Wang. A scholar is included among the top collaborators of Tong 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 Tong Wang. Tong 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
#WorkIndexed citations
1 7
2 1
3 1
4 0
5 2
6 20
7 8
8 8
9 3
10 8
11 12
12
Hybrid Predictive Models: When an Interpretable Model Collaborates with a Black-box Model
21
13
Design and Experimental Verification of a Coaxial Mars Rotorcraft
2
14
Transparency Promotion with Model-Agnostic Linear Competitors
2
15
A Co-evolutionary Method Between Architecture and Code.
1
16 27
17
Multi-value Rule Sets for Interpretable Classification with Feature-Efficient Representations
4
18 2
19 2
20
Research on Agent Resource Conflict Resolution Algorithm Based on Negotiation Theory
0

About Tong Wang

Tong Wang is a scholar working on Mechanical Engineering, Artificial Intelligence and Energy Engineering and Power Technology, having authored 114 papers that have together received 881 indexed citations. Recurring topics across this work include Topic Modeling (8 papers), Advanced materials and composites (6 papers) and Metallurgy and Material Forming (5 papers). The work is most often cited by research in Health Informatics (21 citations), Artificial Intelligence (228 citations) and Mechanical Engineering (251 citations). Tong Wang has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Cynthia Rudin, Yimin Liu, Erica Klampfl, Finale Doshi‐Velez, Huijun Li, Rodrigo C. de Lamare, Paul Mitchell, Stephen van Duin, Bintao Wu and Qihang Lin. Their work appears in journals such as PLoS ONE, Advanced Functional Materials and Journal of Cleaner Production.

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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