Mingming Bai

552 citations
16 papers · 402 indexed · h-index 13

Mingming Bai

16 papers receiving 398 citations

Peers

Mingming Bai
Comparison fields: 5 of 41
  • Artificial Intelligence 310
  • Aerospace Engineering 175
  • Ocean Engineering 67
  • Control and Systems Engineering 92
  • Oceanography 43
Replace Guangle Jia with:
Guangle Jia China
Panlong Wu China
An Li China
Kailong Li China
D. Lerro United States
H. Driessen Netherlands
Roslyn A. Lau Australia
Piotr Kamiński Poland
Jérémie Houssineau United Kingdom
Abhinoy Kumar Singh India
Mingming Bai relative to Guangle Jia China Guangle Jia's profile →
Citations per field
00.5×1.5×2.2×
Guangle Jia · 1×
Citations per year

Countries citing papers authored by Mingming Bai

Since Specialization
Citations

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

Fields of papers citing papers by Mingming Bai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 16 scholars most cited alongside Mingming Bai, 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 Mingming Bai Line = papers co-authored together Mingming Bai links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 20228
2 202220
3 202244
4 202218
5 202136
6 202138
7 202027
8 202018
9 202013
10 202080
11 202026
12 202014
13 201932
14 20191
15 201822
16 20185

About Mingming Bai

Mingming Bai is a scholar working on Artificial Intelligence, Ocean Engineering, Statistics and Probability, Civil and Structural Engineering and Computer Networks and Communications, having authored 16 papers that have together received 402 indexed citations. Recurring topics across this work include Target Tracking and Data Fusion in Sensor Networks (14 papers), Indoor and Outdoor Localization Technologies (4 papers), Underwater Vehicles and Communication Systems (4 papers), Distributed Sensor Networks and Detection Algorithms (3 papers), Water Systems and Optimization (3 papers), GNSS positioning and interference (3 papers), Inertial Sensor and Navigation (3 papers) and Bayesian Methods and Mixture Models (2 papers). The work is most often cited by research in Artificial Intelligence (310 citations), Aerospace Engineering (175 citations), Ocean Engineering (67 citations), Control and Systems Engineering (92 citations) and Oceanography (43 citations). Mingming Bai has collaborated with scholars based in China, United Kingdom and Hong Kong. Frequent co-authors include Yonggang Zhang, Yulong Huang, Guangle Jia, Feng Chen, Badong Chen, Ning Li, Jonathon A. Chambers, Youfu Li, Jonathon A. Chambers and Yang Liu. Their work appears in journals such as IEEE Sensors Journal, Signal Processing, IEEE Transactions on Aerospace and Electronic Systems, IEEE Transactions on Instrumentation and Measurement and Optics Letters.

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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