Shuming Shi
- Artificial Intelligence top 0.5%
- Topic Modeling 106
- Natural Language Processing Techniques 101
- Speech and dialogue systems 11
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- Multimodal Machine Learning Applications 37
- Automotive Engineering top 2%
- Vehicle emissions and performance 16
- Vehicle Dynamics and Control Systems 11
- Information Systems top 1%
- Web Data Mining and Analysis 12
- Health Informatics top 5%
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- Traffic control and management 9
- Journals
- IEEE Transactions on Automatic Control (1 paper)Optics Express (1 paper)IEEE Access (2 papers)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Shuming Shi
176 papers receiving 3.2k citations
Peers
Comparison fields: 5 of 123
- Artificial Intelligence 2.3k
- Computer Vision and Pattern Recognition 644
- Automotive Engineering 358
- Information Systems 547
- Health Informatics 27
Countries citing papers authored by Shuming Shi
This map shows the geographic impact of Shuming Shi'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 Shuming Shi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shuming Shi more than expected).
Fields of papers citing papers by Shuming Shi
This network shows the impact of papers produced by Shuming Shi. 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 Shuming Shi. The network helps show where Shuming Shi may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Shuming Shi, 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 | 2025 | 2 | |
| 2 | 2024 | 48 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 2 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 0 | |
| 7 | 2023 | 4 | |
| 8 | 2023 | 5 | |
| 9 | 2023 | 30 | |
| 10 | 2023 | 1 | |
| 11 | 2022 | 12 | |
| 12 | 2018 | 42 | |
| 13 | 2016 | 83 | |
| 14 | Parameter Identification Method for the Tire Cornering Stiffness of Model Vehicle | 2016 | 2 |
| 15 | 2014 | 0 | |
| 16 | Nonlinear Evidence Fusion and Propagation for Hyponymy Relation Mining | 2011 | 13 |
| 17 | Microsoft Research Asia at the Web Track of TREC 2009 | 2009 | 13 |
| 18 | Microsoft Research Asia at Web Track and Terabyte Track of TREC 2004. | 2004 | 40 |
| 19 | 2004 | 1 | |
| 20 | METHODS OF CALCULATION OF COLLISION VELOCITY OF MOTOR VEHICLES USING THE LAW OF MOMENTUM CONSERVATION | 1997 | 0 |
About Shuming Shi
Shuming Shi is a scholar working on Artificial Intelligence, Automotive Engineering and Computer Vision and Pattern Recognition, having authored 184 papers that have together received 3.4k indexed citations. Recurring topics across this work include Topic Modeling (106 papers), Natural Language Processing Techniques (101 papers), Multimodal Machine Learning Applications (37 papers), Vehicle emissions and performance (16 papers), Web Data Mining and Analysis (12 papers), Vehicle Dynamics and Control Systems (11 papers), Speech and dialogue systems (11 papers) and Traffic control and management (9 papers). The work is most often cited by research in Artificial Intelligence (2.3k citations), Computer Vision and Pattern Recognition (644 citations) and Automotive Engineering (358 citations). Shuming Shi has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Zhaopeng Tu, Xiaojiang Liu, Chin-Yew Lin, Haisong Zhang, Yan Wang, Longyue Wang, Jing Li, Jon Turner, Ji-Rong Wen and Yan Song. Their work appears in journals such as IEEE Transactions on Automatic Control, Optics Express and IEEE Access.
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.