Shaoming Xu

1.5k citations
13 papers · 677 indexed · 2 hit papers · h-index 8

Shaoming Xu

13 papers receiving 653 citations

Hit Papers

Knowledge-guided machine learning can impro...602022202620232024100200300

Peers

Shaoming Xu
Comparison fields: 5 of 108
  • Statistical and Nonlinear Physics 107
  • Environmental Engineering 116
  • Water Science and Technology 78
  • Global and Planetary Change 91
  • Statistics, Probability and Uncertainty 27
Replace Sangchul Lee with:
Sangchul Lee South Korea
Jared Willard United States
C.Y. Liaw Singapore
Minglei Fu China
Yulong Bai China
Haibin Chang China
Shaohua Xu China
Bin Pan China
Fengxiang Jin China
Shaoming Xu relative to Sangchul Lee South Korea Sangchul Lee's profile →
Citations per field
00.5×6.5×
Sangchul Lee · 1×
Citations per year

Countries citing papers authored by Shaoming Xu

Since Specialization
Citations

This map shows the geographic impact of Shaoming 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 Shaoming Xu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shaoming Xu more than expected).

Fields of papers citing papers by Shaoming Xu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shaoming 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 Shaoming Xu. The network helps show where Shaoming Xu may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Shaoming Xu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Shaoming Xu Line = papers co-authored together Shaoming Xu links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1 20241
2
Knowledge-guided machine learning can improve carbon cycle quantification in agroecosystemsbreakdown →
202460
3 20232
4 202317
5 20233
6
Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systemsbreakdown →
2022317
7 202233
8 202214
9 202225
10 20212
11 20213
12
Integrating Physics-Based Modeling with Machine Learning: A Survey
2020187
13 201913

About Shaoming Xu

Shaoming Xu is a scholar working on Environmental Chemistry, Statistical and Nonlinear Physics and Plant Science, having authored 13 papers that have together received 677 indexed citations. Recurring topics across this work include Plant nutrient uptake and metabolism (6 papers), Legume Nitrogen Fixing Symbiosis (4 papers), Plant Molecular Biology Research (3 papers), Soil and Water Nutrient Dynamics (2 papers), Plant Stress Responses and Tolerance (2 papers), Climate change impacts on agriculture (2 papers), Hydrology and Watershed Management Studies (2 papers) and Computational Physics and Python Applications (2 papers). The work is most often cited by research in Statistical and Nonlinear Physics (107 citations), Environmental Engineering (116 citations) and Water Science and Technology (78 citations). Shaoming Xu has collaborated with scholars based in United States, China and Denmark. Frequent co-authors include Xiaowei Jia, Vipin Kumar, Michael Steinbach, Jared Willard, Kaiyu Guan, Zhenong Jin, Licheng Liu, Bin Peng, Jinyun Tang and Wang Zhou. Their work appears in journals such as Journal of Experimental Botany, International Journal of Molecular Sciences, Water Resources Research, Geoscientific model development and Nature Communications.

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.

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