Pingchuan Ma
Impact in
Papers in
-
- Topic Modeling 5
- Adversarial Robustness in Machine Learning 5
- Bayesian Modeling and Causal Inference 5
-
- Luminescence Properties of Advanced Materials 11
- Co-authors
- Yanhua Song (10 shared papers)Ye Sheng (11 shared papers)Haifeng Zou (11 shared papers)Chengyi Xu (6 shared papers)Keyan Zheng (9 shared papers)Bo Yuan (7 shared papers)Shuai Wang (18 shared papers)Shuai Wang (1 shared paper)
- Journals
- Advanced Materials (2 papers)RSC Advances (2 papers)Proceedings of the VLDB Endowment (2 papers)Optical Materials (2 papers)Journal of Alloys and Compounds (2 papers)
- Partner nations
- ChinaHong KongUnited States
In The Last Decade
Pingchuan Ma
60 papers receiving 885 citations
Peers
Comparison fields: 5 of 100
- Software 60
- Radiation 90
- Materials Chemistry 367
- Ceramics and Composites 45
- Signal Processing 78
Countries citing papers authored by Pingchuan Ma
This map shows the geographic impact of Pingchuan Ma'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 Pingchuan Ma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pingchuan Ma more than expected).
Fields of papers citing papers by Pingchuan Ma
This network shows the impact of papers produced by Pingchuan Ma. 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 Pingchuan Ma. The network helps show where Pingchuan Ma may publish in the future.
Co-authors
The 25 scholars most cited alongside Pingchuan Ma, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 67 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 80 | |
| 2 | 2020 | 69 | |
| 3 | 2020 | 63 | |
| 4 | 2024 | 50 | |
| 5 | 2021 | 48 | |
| 6 | 2017 | 44 | |
| 7 | 2016 | 40 | |
| 8 | 2023 | 34 | |
| 9 | 2017 | 33 | |
| 10 | 2016 | 32 | |
| 11 | 2016 | 31 | |
| 12 | 2017 | 30 | |
| 13 | 2016 | 23 | |
| 14 | 2022 | 23 | |
| 15 | 2015 | 22 | |
| 16 | 2021 | 20 | |
| 17 | 2021 | 17 | |
| 18 | 2021 | 16 | |
| 19 | 2022 | 16 | |
| 20 | 2023 | 13 |
About Pingchuan Ma
Pingchuan Ma is a scholar working on Artificial Intelligence, Materials Chemistry, Information Systems, Signal Processing and Electrical and Electronic Engineering, having authored 67 papers that have together received 898 indexed citations. Recurring topics across this work include Luminescence Properties of Advanced Materials (11 papers), Software Testing and Debugging Techniques (7 papers), Advanced Malware Detection Techniques (7 papers), Software Engineering Research (7 papers), Data Quality and Management (5 papers), Topic Modeling (5 papers), Adversarial Robustness in Machine Learning (5 papers) and Bayesian Modeling and Causal Inference (5 papers). The work is most often cited by research in Software (60 citations), Radiation (90 citations), Materials Chemistry (367 citations), Ceramics and Composites (45 citations) and Signal Processing (78 citations). Pingchuan Ma has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Yanhua Song, Ye Sheng, Haifeng Zou, Chengyi Xu, Keyan Zheng, Bo Yuan, Shuai Wang, Shuai Wang, Jin Liu and Hongxia Guan. Their work appears in journals such as Advanced Materials, RSC Advances, Proceedings of the VLDB Endowment, Optical Materials and Journal of Alloys and Compounds.
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.