Haiping Ma

1.1k citations
38 papers · 709 indexed · h-index 15
Topics
Intelligent Tutoring Systems and Adaptive Learning (9 papers)Advanced Multi-Objective Optimization Algorithms (7 papers)Metaheuristic Optimization Algorithms Research (7 papers)
Partner nations
ChinaHong KongGermany

In The Last Decade

Haiping Ma

35 papers receiving 700 citations

Peers

Haiping Ma
Comparison fields: 5 of 108
  • Artificial Intelligence 340
  • Computational Theory and Mathematics 224
  • Molecular Biology 62
  • Information Systems 62
  • Surgery 59
Replace Dexian Wang with:
Dexian Wang China
Georgios Theocharous United States
Rein Houthooft Belgium
Amir Masoud Eftekhari Moghadam Iran
Javad Akbari Torkestani Iran
Xiubin Zhu China
S. K. Smit Netherlands
Armando Tacchella Italy
Yuanjian Zhang China
Zhiyong Hong China
Haiping Ma relative to Dexian Wang China Dexian Wang's profile →
Citations per field
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Dexian Wang · 1×
Citations per year

Countries citing papers authored by Haiping Ma

Since Specialization
Citations

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

Fields of papers citing papers by Haiping Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Haiping Ma

This figure shows the co-authorship network connecting the top 25 collaborators of Haiping Ma. A scholar is included among the top collaborators of Haiping Ma based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Haiping Ma. Haiping Ma is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 1
3 0
4 0
5 6
6 10
7 13
8 5
9 7
10 3
11 2
12 8
13 12
14 21
15 20
16 35
17 111
18 13
19 3
20 103

About Haiping Ma

Haiping Ma is a scholar working on Computer Science Applications, Health Informatics and Artificial Intelligence, having authored 38 papers that have together received 709 indexed citations. Recurring topics across this work include Intelligent Tutoring Systems and Adaptive Learning (9 papers), Advanced Multi-Objective Optimization Algorithms (7 papers) and Metaheuristic Optimization Algorithms Research (7 papers). The work is most often cited by research in Computational Theory and Mathematics (224 citations), Artificial Intelligence (340 citations) and Computer Science Applications (26 citations). Haiping Ma has collaborated with scholars based in China, Hong Kong and Germany. Frequent co-authors include Xingyi Zhang, Ye Tian, Yaochu Jin, Kay Chen Tan, Xiaopeng Li, Lei Zhang, Hong Zheng, Lin Chen, Hai Guo and Ye Tian. Their work appears in journals such as Meat Science, IEEE Transactions on Evolutionary Computation and IEEE Transactions on Neural Networks and Learning Systems.

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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