Qin Lu

675 total citations
60 papers, 456 citations indexed

About

Qin Lu is a scholar working on Artificial Intelligence, Computer Networks and Communications and Aerospace Engineering. According to data from OpenAlex, Qin Lu has authored 60 papers receiving a total of 456 indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Artificial Intelligence, 11 papers in Computer Networks and Communications and 10 papers in Aerospace Engineering. Recurrent topics in Qin Lu's work include Gaussian Processes and Bayesian Inference (15 papers), Target Tracking and Data Fusion in Sensor Networks (12 papers) and Distributed Sensor Networks and Detection Algorithms (9 papers). Qin Lu is often cited by papers focused on Gaussian Processes and Bayesian Inference (15 papers), Target Tracking and Data Fusion in Sensor Networks (12 papers) and Distributed Sensor Networks and Detection Algorithms (9 papers). Qin Lu collaborates with scholars based in United States, China and Sweden. Qin Lu's co-authors include Georgios B. Giannakis, Wei Zhang, Wei Zhang, Peter Willett, Yaakov Bar‐Shalom, Jin Zhu, Vassilis N. Ioannidis, Yanning Shen, Amvrossios C. Bagtzoglou and Zhi Sun and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Advanced Functional Materials and The Journal of Comparative Neurology.

In The Last Decade

Qin Lu

56 papers receiving 438 citations

Peers

Qin Lu
Comparison fields: 5 of 92
  • Artificial Intelligence 165
  • Electrical and Electronic Engineering 80
  • Civil and Structural Engineering 66
  • Aerospace Engineering 61
  • Computer Networks and Communications 56
Replace Weibin Liu with:
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Cissi Y. Lin Taiwan
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Xin Zheng China
Jize Zhang United States
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Weibin Liu China View profile →
Citations per field, relative to Qin Lu
Qin Lu · 1×
Citations per year, relative to Qin Lu
Qin Lu · 1×

Countries citing papers authored by Qin Lu

Since Specialization
Citations

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

Fields of papers citing papers by Qin Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qin Lu

This figure shows the co-authorship network connecting the top 25 collaborators of Qin Lu. A scholar is included among the top collaborators of Qin Lu 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 Qin Lu. Qin Lu 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 1
2 2
3 5
4 11
5 7
6 6
7 31
8 11
9 2
10 6
11 5
12 8
13 3
14 10
15
Ensemble Gaussian Processes with Spectral Features for Online Interactive Learning with Scalability.
23
16 6
17 7
18 6
19 8
20 11

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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