Simeng Han
Impact in
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- Plant nutrient uptake and metabolism
- Legume Nitrogen Fixing Symbiosis
- Plant Molecular Biology Research
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- Hemophilia Treatment and Research
Papers in
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- Topic Modeling 5
- Natural Language Processing Techniques 5
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- Hemophilia Treatment and Research 2
- Co-authors
- Jun S. Liu (1 shared paper)Ke Deng (1 shared paper)Marielle Adrian (2 shared papers)Frédéric Cointault (2 shared papers)Sophie Trouvelot (2 shared papers)Christophe Salon (2 shared papers)Marion Prudent (1 shared paper)Werner Reinartz (1 shared paper)
- Journals
- Frontiers in Plant Science (1 paper)Journal of Medical Economics (1 paper)Advances in Therapy (1 paper)Plant Methods (1 paper)Frontiers of Environmental Science & Engineering (1 paper)
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Simeng Han
12 papers receiving 233 citations
Peers
Comparison fields: 5 of 58
- Plant Science 96
- Hematology 20
- Agronomy and Crop Science 18
- Artificial Intelligence 54
- Health Informatics 2
Countries citing papers authored by Simeng Han
This map shows the geographic impact of Simeng Han'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 Simeng Han with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Simeng Han more than expected).
Fields of papers citing papers by Simeng Han
This network shows the impact of papers produced by Simeng Han. 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 Simeng Han. The network helps show where Simeng Han may publish in the future.
Co-authors
The 25 scholars most cited alongside Simeng Han, 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 | 2016 | 89 | |
| 2 | 2014 | 40 | |
| 3 | 2023 | 34 | |
| 4 | 2021 | 17 | |
| 5 | 2018 | 17 | |
| 6 | 2020 | 16 | |
| 7 | 2021 | 11 | |
| 8 | 2024 | 6 | |
| 9 | 2018 | 4 | |
| 10 | 2018 | 2 | |
| 11 | 2021 | 2 | |
| 12 | 2023 | 1 | |
| 13 | 2025 | 0 | |
| 14 | 2024 | 0 |
About Simeng Han
Simeng Han is a scholar working on Artificial Intelligence, Hematology, Plant Science, Urology and Marketing, having authored 14 papers that have together received 239 indexed citations. Recurring topics across this work include Topic Modeling (5 papers), Natural Language Processing Techniques (5 papers), Hemophilia Treatment and Research (2 papers), Plant nutrient uptake and metabolism (2 papers), Computational and Text Analysis Methods (1 paper), Fuzzy Systems and Optimization (1 paper), Membrane Separation Technologies (1 paper) and Multi-Criteria Decision Making (1 paper). The work is most often cited by research in Plant Science (96 citations), Hematology (20 citations), Agronomy and Crop Science (18 citations), Artificial Intelligence (54 citations) and Health Informatics (2 citations). Simeng Han has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Jun S. Liu, Ke Deng, Marielle Adrian, Frédéric Cointault, Sophie Trouvelot, Christophe Salon, Marion Prudent, Werner Reinartz, Yixin Liu and Christian Jeudy. Their work appears in journals such as Frontiers in Plant Science, Journal of Medical Economics, Advances in Therapy, Plant Methods and Frontiers of Environmental Science & Engineering.
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.