Cong Ma
Impact in
- Pollution top 5%
- Pharmaceutical and Antibiotic Environmental Impacts
-
- Water Treatment and Disinfection
- Effects and risks of endocrine disrupting chemicals
Papers in
-
- Handwritten Text Recognition Techniques 7
- Multimodal Machine Learning Applications 5
- Chaos-based Image/Signal Encryption 2
-
- Natural Language Processing Techniques 9
- Topic Modeling 2
- Co-authors
- Chang‐Ping Yu (5 shared papers)Qian Sun (4 shared papers)Xiaoqing Xie (1 shared paper)Mingyue Li (1 shared paper)Chengqing Zong (9 shared papers)Haoran Li (2 shared papers)Junnan Zhu (2 shared papers)Jiajun Zhang (3 shared papers)
In The Last Decade
Cong Ma
25 papers receiving 554 citations
Peers
Comparison fields: 5 of 98
- Pollution 268
- Health, Toxicology and Mutagenesis 142
- Analytical Chemistry 68
- Applied Microbiology and Biotechnology 10
- Computer Vision and Pattern Recognition 99
Countries citing papers authored by Cong Ma
This map shows the geographic impact of Cong 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 Cong Ma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cong Ma more than expected).
Fields of papers citing papers by Cong Ma
This network shows the impact of papers produced by Cong 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 Cong Ma. The network helps show where Cong Ma may publish in the future.
Co-authors
The 25 scholars most cited alongside Cong 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 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 223 | |
| 2 | 2017 | 79 | |
| 3 | 2018 | 56 | |
| 4 | 2015 | 43 | |
| 5 | 2019 | 42 | |
| 6 | 2021 | 36 | |
| 7 | 2016 | 23 | |
| 8 | 2022 | 13 | |
| 9 | 2024 | 6 | |
| 10 | 2023 | 6 | |
| 11 | 2023 | 5 | |
| 12 | 2023 | 4 | |
| 13 | 2023 | 3 | |
| 14 | 2022 | 3 | |
| 15 | 2024 | 3 | |
| 16 | 2023 | 3 | |
| 17 | 2013 | 3 | |
| 18 | 2025 | 2 | |
| 19 | 2023 | 2 | |
| 20 | 2024 | 2 |
About Cong Ma
Cong Ma is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Pollution, Molecular Biology and Health, Toxicology and Mutagenesis, having authored 26 papers that have together received 562 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (9 papers), Handwritten Text Recognition Techniques (7 papers), Multimodal Machine Learning Applications (5 papers), Pharmaceutical and Antibiotic Environmental Impacts (5 papers), Analytical chemistry methods development (2 papers), Chaos-based Image/Signal Encryption (2 papers), Topic Modeling (2 papers) and Effects and risks of endocrine disrupting chemicals (2 papers). The work is most often cited by research in Pollution (268 citations), Health, Toxicology and Mutagenesis (142 citations), Analytical Chemistry (68 citations), Applied Microbiology and Biotechnology (10 citations) and Computer Vision and Pattern Recognition (99 citations). Cong Ma has collaborated with scholars based in China, Australia and Germany. Frequent co-authors include Chang‐Ping Yu, Qian Sun, Xiaoqing Xie, Mingyue Li, Chengqing Zong, Haoran Li, Junnan Zhu, Jiajun Zhang, Dan Qin and Fangfang Zhang. Their work appears in journals such as Current Microbiology, Biosensors, IEEE Transactions on Pattern Analysis and Machine Intelligence, Chemosphere and Environmental Pollution.
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.