Meiyi Ma

604 total citations
37 papers, 330 citations indexed

About

Meiyi Ma is a scholar working on Artificial Intelligence, Computer Networks and Communications and Computer Vision and Pattern Recognition. According to data from OpenAlex, Meiyi Ma has authored 37 papers receiving a total of 330 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 11 papers in Computer Networks and Communications and 8 papers in Computer Vision and Pattern Recognition. Recurrent topics in Meiyi Ma's work include Context-Aware Activity Recognition Systems (7 papers), Smart Cities and Technologies (6 papers) and Mobile Crowdsensing and Crowdsourcing (5 papers). Meiyi Ma is often cited by papers focused on Context-Aware Activity Recognition Systems (7 papers), Smart Cities and Technologies (6 papers) and Mobile Crowdsensing and Crowdsourcing (5 papers). Meiyi Ma collaborates with scholars based in United States, Sweden and China. Meiyi Ma's co-authors include John A. Stankovic, Sarah Masud Preum, Lu Feng, William Tärneberg, Mohsin Y Ahmed, Hongning Wang, David J. Stone, Ezio Bartocci, Abdeltawab Hendawi and Eli Lifland and has published in prestigious journals such as ACM Computing Surveys, Computer and Journal of Advanced Nursing.

In The Last Decade

Meiyi Ma

37 papers receiving 322 citations

Peers

Meiyi Ma
Comparison fields: 5 of 76
  • Artificial Intelligence 111
  • Computer Networks and Communications 95
  • Computer Vision and Pattern Recognition 60
  • Information Systems 45
  • Media Technology 38
Sarah Masud Preum United States
Manish Mathuria India
Ngo Tung Son Vietnam
Mideth Abisado Philippines
Amadeo-José Argüelles-Cruz Mexico
Ibtisam A. Aljazaery Iraq
Giovanni Adorni Italy
Diego Gachet Páez Spain
Sanjay Jasola India
Sarah Masud Preum United States View profile →
Citations per field, relative to Meiyi Ma
Meiyi Ma · 1×
Citations per year, relative to Meiyi Ma
Meiyi Ma · 1×

Countries citing papers authored by Meiyi Ma

Since Specialization
Citations

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

Fields of papers citing papers by Meiyi Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Meiyi Ma

This figure shows the co-authorship network connecting the top 25 collaborators of Meiyi Ma. A scholar is included among the top collaborators of Meiyi 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 Meiyi Ma. Meiyi 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
# Work Indexed citations
1 2
2 1
3 1
4 1
5 1
6 9
7 7
8 1
9 7
10 24
11
STLnet: Signal Temporal Logic Enforced Multivariate Recurrent Neural Networks
11
12 2
13 6
14 8
15 19
16 1
17
Detection of Runtime Conflicts among Services in Smart Cities
17
18
Social Group Search Optimizer algorithm for ad hoc network
1
19
Path Planning for Mobile Robots Based on Social Group Search Algorithm
5
20 1

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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