Bailu Wang

893 citations
35 papers · 617 indexed · h-index 12

Impact in

Papers in

Bailu Wang

31 papers receiving 598 citations

Peers

Bailu Wang
Comparison fields: 5 of 50
  • Artificial Intelligence 511
  • Computer Networks and Communications 354
  • Aerospace Engineering 147
  • Control and Systems Engineering 121
  • Signal Processing 36
Replace Marcel L. Hernandez with:
Marcel L. Hernandez United Kingdom
Zhanlue Zhao United States
Feng Yang China
Michael Beard Australia
Constantino Rago United States
Ondrej Hlinka Austria
H. Driessen Netherlands
J.A. Roecker United States
Shozo Mori United States
Alexander Charlish Germany
Bailu Wang relative to Marcel L. Hernandez United Kingdom Marcel L. Hernandez's profile →
Citations per field
00.5×3.2×
Marcel L. Hernandez · 1×
Citations per year

Countries citing papers authored by Bailu Wang

Since Specialization
Citations

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

Fields of papers citing papers by Bailu Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20241
3 20249
4 20220
5 20228
6 202221
7 20228
8 20221
9 20211
10 20212
11 201959
12 201882
13 201746
14 201755
15 201793
16 2016101
17
Distributed multi-target tracking via generalized multi-Bernoulli random finite sets
201510
18 20141
19 20145
20 20131

About Bailu Wang

Bailu Wang is a scholar working on Artificial Intelligence, Signal Processing, Computer Networks and Communications, Aerospace Engineering and Control and Systems Engineering, having authored 35 papers that have together received 617 indexed citations. Recurring topics across this work include Target Tracking and Data Fusion in Sensor Networks (24 papers), Distributed Sensor Networks and Detection Algorithms (13 papers), Indoor and Outdoor Localization Technologies (7 papers), Gaussian Processes and Bayesian Inference (7 papers), Advanced SAR Imaging Techniques (6 papers), Radar Systems and Signal Processing (6 papers), Direction-of-Arrival Estimation Techniques (5 papers) and Fault Detection and Control Systems (3 papers). The work is most often cited by research in Artificial Intelligence (511 citations), Computer Networks and Communications (354 citations), Aerospace Engineering (147 citations), Control and Systems Engineering (121 citations) and Signal Processing (36 citations). Bailu Wang has collaborated with scholars based in China, Italy and Australia. Frequent co-authors include Suqi Li, Wei Yi, Lingjiang Kong, Reza Hoseinnezhad, Giorgio Battistelli, Luigi Chisci, Xiaobo Yang, Nicola Forti, Bruno Sinopoli and Guchong Li. Their work appears in journals such as IEEE Transactions on Signal Processing, Signal Processing, IET Radar Sonar & Navigation, IEEE Transactions on Signal and Information Processing over Networks and IEEE Wireless Communications 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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