Mingyu Wang

417 citations
11 papers · 267 · h-index 7

Impact in

Papers in

Mingyu Wang

11 papers receiving 259 citations

Peers

Mingyu Wang
Comparison fields: 5 of 41
  • Automotive Engineering 123
  • Computer Vision and Pattern Recognition 100
  • Control and Systems Engineering 100
  • Artificial Intelligence 79
  • Computer Networks and Communications 44
Replace Yangang Ren with:
Yangang Ren China
David Fridovich-Keil United States
Negar Mehr United States
Shalin Mehta United States
Elad H. Kivelevitch United States
Jens Oehlerking Germany
Jilles Dibangoye France
Yash Vardhan Pant United States
Zhenghao Peng United States
Karen Leung United States
Mingyu Wang relative to Yangang Ren China Yangang Ren's profile →
Citations per field
00.5×1.5×2.0×
Yangang Ren · 1×
Citations per year

Countries citing papers authored by Mingyu Wang

Since Specialization
Citations

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

Fields of papers citing papers by Mingyu Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 13 scholars most cited alongside Mingyu Wang, 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 Mingyu Wang Line = papers co-authored together Mingyu Wang links everyone, so they are left out of the graph.

All Works

11 of 11 papers shown
#Work
1 202189
2 201932
3 201928
4 202027
5 202327
6 201827
7 202024
8 20205
9 20225
10 20112
11 20101

About Mingyu Wang

Mingyu Wang is a scholar working on Automotive Engineering, Control and Systems Engineering, Computer Vision and Pattern Recognition, Management Science and Operations Research and Economics and Econometrics, having authored 11 papers that have together received 267 indexed citations. Recurring topics across this work include Traffic control and management (4 papers), Autonomous Vehicle Technology and Safety (3 papers), Robotic Path Planning Algorithms (3 papers), Game Theory and Applications (2 papers), Reinforcement Learning in Robotics (2 papers), Game Theory and Voting Systems (2 papers), Extremum Seeking Control Systems (1 paper) and Advanced Control Systems Optimization (1 paper). The work is most often cited by research in Automotive Engineering (123 citations), Computer Vision and Pattern Recognition (100 citations), Control and Systems Engineering (100 citations), Artificial Intelligence (79 citations) and Computer Networks and Communications (44 citations). Mingyu Wang has collaborated with scholars based in United States and China. Frequent co-authors include Mac Schwager, Zijian Wang, J. Christian Gerdes, John M. Talbot, Negar Mehr, Magnus Egerstedt, Gennaro Notomista, Adrien Gaidon, Jiuqiang Liu and Haoming Wang. Their work appears in journals such as IEEE Transactions on Robotics, Journal of Fixed Point Theory and Applications, 2022 International Conference on Robotics and Automation (ICRA) and 2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery.

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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