M.L. Kuang
Impact in
- Automotive Engineering top 2%
- Electric and Hybrid Vehicle Technologies
- Advanced Battery Technologies Research
- Vehicle emissions and performance
- Vehicle Dynamics and Control Systems
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- Electric Vehicles and Infrastructure
Papers in
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- Electric and Hybrid Vehicle Technologies 7
- Advanced Battery Technologies Research 3
- Vehicle emissions and performance 2
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- Electric Vehicles and Infrastructure 4
- Advanced Fiber Optic Sensors 1
- Co-authors
- Anastasia Phillips (3 shared papers)Yi Lu Murphey (3 shared papers)M. Abul Masrur (2 shared papers)Jungme Park (2 shared papers)Hao Ying (2 shared papers)Fazal Syed (2 shared papers)Zhihang Chen (1 shared paper)Shuhei Okubo (1 shared paper)
- Partner nations
- United StatesChinaCanada
In The Last Decade
M.L. Kuang
9 papers receiving 472 citations
Peers
Comparison fields: 5 of 42
- Automotive Engineering 395
- Electrical and Electronic Engineering 298
- Fluid Flow and Transfer Processes 28
- Control and Systems Engineering 99
- Mechanical Engineering 83
Countries citing papers authored by M.L. Kuang
This map shows the geographic impact of M.L. Kuang'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 M.L. Kuang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M.L. Kuang more than expected).
Fields of papers citing papers by M.L. Kuang
This network shows the impact of papers produced by M.L. Kuang. 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 M.L. Kuang. The network helps show where M.L. Kuang may publish in the future.
Co-authors
The 19 scholars most cited alongside M.L. Kuang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 170 | |
| 2 | 2009 | 102 | |
| 3 | 2009 | 78 | |
| 4 | 2009 | 78 | |
| 5 | 2011 | 31 | |
| 6 | 1999 | 19 | |
| 7 | Neural Learning of Predicting Driving Environment | 2008 | 12 |
| 8 | 2017 | 4 | |
| 9 | 2018 | 1 | |
| 10 | 2025 | 0 |
About M.L. Kuang
M.L. Kuang is a scholar working on Automotive Engineering, Electrical and Electronic Engineering, Mechanical Engineering, Control and Systems Engineering and Atomic and Molecular Physics, and Optics, having authored 10 papers that have together received 495 indexed citations. Recurring topics across this work include Electric and Hybrid Vehicle Technologies (7 papers), Electric Vehicles and Infrastructure (4 papers), Advanced Battery Technologies Research (3 papers), Control Systems in Engineering (3 papers), Vehicle emissions and performance (2 papers), Iterative Learning Control Systems (2 papers), Hydraulic and Pneumatic Systems (1 paper) and Advanced Fiber Optic Sensors (1 paper). The work is most often cited by research in Automotive Engineering (395 citations), Electrical and Electronic Engineering (298 citations), Fluid Flow and Transfer Processes (28 citations), Control and Systems Engineering (99 citations) and Mechanical Engineering (83 citations). M.L. Kuang has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Anastasia Phillips, Yi Lu Murphey, M. Abul Masrur, Jungme Park, Hao Ying, Fazal Syed, Zhihang Chen, Shuhei Okubo, Zhihang Chen and Stefano Di Cairano. Their work appears in journals such as IEEE Transactions on Vehicular Technology and Photonics.
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.