Hong Cheng
- Computational Mathematics top 1%
- Microbiology top 2%
- Pollution top 5%
- Wastewater Treatment and Nitrogen Removal 15
- Transportation top 2%
- Family Practice top 5%
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- Membrane Separation Technologies 14
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- Sparse and Compressive Sensing Techniques 9
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- Prosthetics and Rehabilitation Robotics 9
- Muscle activation and electromyography studies 6
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- Data Quality and Management 9
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- Water Treatment and Disinfection 7
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- Carcinogens and Genotoxicity Assessment 6
- Co-authors
- Pei‐Ying HongElizabeth DelzellMaurizio MacalusoJames ChengFanhua ShangYuanyuan LiuJeffrey R. CurtisKenneth G. Saag
- Journals
- Proceedings of the National Academy of Sciences (1 paper)Journal of the American Chemical Society (1 paper)Environmental Science & Technology (2 papers)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Hong Cheng
111 papers receiving 2.8k citations
Peers
Comparison fields: 5 of 178
- Computational Mathematics 119
- Microbiology 219
- Pollution 332
- Transportation 190
- Family Practice 60
Countries citing papers authored by Hong Cheng
This map shows the geographic impact of Hong Cheng'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 Hong Cheng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hong Cheng more than expected).
Fields of papers citing papers by Hong Cheng
This network shows the impact of papers produced by Hong Cheng. 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 Hong Cheng. The network helps show where Hong Cheng may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Hong Cheng, 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 | 3 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2025 | 1 | |
| 5 | 2024 | 0 | |
| 6 | 2024 | 15 | |
| 7 | 2024 | 4 | |
| 8 | 2024 | 11 | |
| 9 | 2023 | 23 | |
| 10 | 2023 | 0 | |
| 11 | 2023 | 3 | |
| 12 | 2021 | 23 | |
| 13 | 2019 | 3 | |
| 14 | Accelerated First-order Methods for Geodesically Convex Optimization on Riemannian Manifolds | 2017 | 19 |
| 15 | 2013 | 155 | |
| 16 | 2013 | 15 | |
| 17 | An intelligent RFID data predicting method based on BP-adaboost | 2012 | 2 |
| 18 | Stock risk mining by news | 2010 | 1 |
| 19 | 2008 | 95 | |
| 20 | Planning for marketing campaigns | 2003 | 2 |
About Hong Cheng
Hong Cheng is a scholar working on Computational Mathematics, Pollution and Water Science and Technology, having authored 122 papers that have together received 2.9k indexed citations. Recurring topics across this work include Wastewater Treatment and Nitrogen Removal (15 papers), Membrane Separation Technologies (14 papers), Sparse and Compressive Sensing Techniques (9 papers), Prosthetics and Rehabilitation Robotics (9 papers), Data Quality and Management (9 papers), Water Treatment and Disinfection (7 papers), Carcinogens and Genotoxicity Assessment (6 papers) and Muscle activation and electromyography studies (6 papers). The work is most often cited by research in Computational Mathematics (119 citations), Microbiology (219 citations) and Pollution (332 citations). Hong Cheng has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Pei‐Ying Hong, Elizabeth Delzell, Maurizio Macaluso, James Cheng, Fanhua Shang, Yuanyuan Liu, Jeffrey R. Curtis, Kenneth G. Saag, Edward W. Hook and Laura H. Bachmann. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Environmental Science & Technology.
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.