Ming Ma

28 papers receiving 306 citations

Peers

Ming Ma
Comparison fields: 5 of 87
  • Modeling and Simulation 30
  • Statistics and Probability 43
  • Public Health, Environmental and Occupational Health 109
  • Genetics 81
  • Marketing 24
Replace Mukesh Kumar with:
Mukesh Kumar India
Rinaldo B. Schinazi United States
Patricia Román‐Román Spain
Ariel Cintrón-Arias United States
Francisco Torres‐Ruiz Spain
Kieran Alden United Kingdom
Luca Guerrini Italy
Nicolas Lanchier United States
Daniela Morale Italy
Claude Lefèvre Belgium
Ming Ma relative to Mukesh Kumar India Mukesh Kumar's profile →
Citations per field
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Mukesh Kumar · 1×
Citations per year

Countries citing papers authored by Ming Ma

Since Specialization
Citations

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

Fields of papers citing papers by Ming Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ming Ma, 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 Ming Ma Line = papers co-authored together Ming Ma links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202172
2 201928
3 201922
4 200722
5 201020
6 202019
7 201917
8 201912
9 201911
10 202210
11 201910
12 20239
13 20189
14 20088
15 19907
16 20137
17 20245
18 19905
19 20224
20 20254

About Ming Ma

Ming Ma is a scholar working on Public Health, Environmental and Occupational Health, Genetics, Statistics and Probability, Computer Networks and Communications and Electrical and Electronic Engineering, having authored 33 papers that have together received 316 indexed citations. Recurring topics across this work include Mathematical and Theoretical Epidemiology and Ecology Models (10 papers), Evolution and Genetic Dynamics (9 papers), Statistical Distribution Estimation and Applications (5 papers), Nonlinear Dynamics and Pattern Formation (5 papers), Catalytic Processes in Materials Science (3 papers), Consumer Market Behavior and Pricing (3 papers), Catalysts for Methane Reforming (2 papers) and Customer churn and segmentation (2 papers). The work is most often cited by research in Modeling and Simulation (30 citations), Statistics and Probability (43 citations), Public Health, Environmental and Occupational Health (109 citations), Genetics (81 citations) and Marketing (24 citations). Ming Ma has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Yong Ye, Yumei Wei, Zehui Li, Wenzhao Liu, Rujia Mi, Huiyong Shen, Xi Shen, Yimin Jiang, Yueguo Wu and Jinyuan Chen. Their work appears in journals such as Advances in Difference Equations, International Journal of Hydrogen Energy, Archives of Osteoporosis, Journal of Statistical Computation and Simulation and Mathematical Biosciences & 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.

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