Mingjie Xu
- Media Technology top 5%
-
- Radiomics and Machine Learning in Medical Imaging 6
- COVID-19 diagnosis using AI 3
- MRI in cancer diagnosis 2
- Modeling and Simulation top 10%
- Electrochemistry top 10%
-
- Lung Cancer Diagnosis and Treatment 4
-
- Energy Harvesting in Wireless Networks 2
-
- IoT and Edge/Fog Computing 2
-
- Cloud Computing and Resource Management 2
-
- Multimodal Machine Learning Applications 2
- Co-authors
- Monika AroraPakorn WatanachaturapornPramod K. VarshneyWei HeJ.H. HuangGuangming LiXin MaChristopher Huang
- Cited by
- Industrial and Manufacturing EngineeringMedia TechnologyRadiology, Nuclear Medicine and Imaging
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Mingjie Xu
27 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 163
- Industrial and Manufacturing Engineering 266
- Media Technology 106
- Radiology, Nuclear Medicine and Imaging 263
- Modeling and Simulation 36
- Electrochemistry 46
Countries citing papers authored by Mingjie Xu
This map shows the geographic impact of Mingjie Xu'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 Mingjie Xu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mingjie Xu more than expected).
Fields of papers citing papers by Mingjie Xu
This network shows the impact of papers produced by Mingjie Xu. 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 Mingjie Xu. The network helps show where Mingjie Xu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Mingjie Xu, 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 | 0 | |
| 2 | 2024 | 3 | |
| 3 | 2023 | 3 | |
| 4 | 2023 | 1 | |
| 5 | 2021 | 86 | |
| 6 | 2020 | 2 | |
| 7 | 2020 | 1 | |
| 8 | 2019 | 68 | |
| 9 | 2019 | 81 | |
| 10 | 2019 | 52 | |
| 11 | 2018 | 35 | |
| 12 | 2018 | 44 | |
| 13 | 2017 | 1 | |
| 14 | 2014 | 19 | |
| 15 | 2014 | 6 | |
| 16 | 2013 | 20 | |
| 17 | 2011 | 13 | |
| 18 | 2006 | 282 | |
| 19 | Decision tree regression for soft classification of remote sensing databreakdown → | 2005 | 477 |
| 20 | 2003 | 33 |
About Mingjie Xu
Mingjie Xu is a scholar working on Transplantation, Media Technology, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Modeling and Simulation, having authored 29 papers that have together received 1.5k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (6 papers), Lung Cancer Diagnosis and Treatment (4 papers), COVID-19 diagnosis using AI (3 papers), Energy Harvesting in Wireless Networks (2 papers), MRI in cancer diagnosis (2 papers), IoT and Edge/Fog Computing (2 papers), Cloud Computing and Resource Management (2 papers) and Multimodal Machine Learning Applications (2 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (266 citations), Media Technology (106 citations), Radiology, Nuclear Medicine and Imaging (263 citations), Modeling and Simulation (36 citations) and Electrochemistry (46 citations). Mingjie Xu has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Monika Arora, Pakorn Watanachaturaporn, Pramod K. Varshney, Wei He, J.H. Huang, Guangming Li, Xin Ma, Christopher Huang, Shanglong Peng and Qiang Zhu. Their work appears in journals such as BioMedical Engineering OnLine, IEEE Access, Virus Research, Scientific Reports and Journal of Advanced Transportation.
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.