Fei Zhu

2.9k citations
97 papers · 1.7k indexed · 1 hit paper · h-index 18
Topics
Reinforcement Learning in Robotics (19 papers)Computational Drug Discovery Methods (15 papers)Machine Learning in Bioinformatics (11 papers)

In The Last Decade

Fei Zhu

87 papers receiving 1.7k citations

Hit Papers

Electrocardiogram generation with a bidirectional LSTM-CN...20192026202120232019100200300400

Peers

Fei Zhu
Comparison fields: 5 of 182
  • Molecular Biology 621
  • Artificial Intelligence 371
  • Cellular and Molecular Neuroscience 296
  • Cognitive Neuroscience 221
  • Cardiology and Cardiovascular Medicine 182
Replace Rubén Armañanzas with:
Rubén Armañanzas Spain
Lihua Li China
Lei Cai China
Sidong Liu Australia
Wei Zeng China
Salvador Durá-Bernal United States
Vı́ctor Robles Spain
Derek Rose United States
Jinzhu Yang China
Alessandro Bria Italy
Fei Zhu relative to Rubén Armañanzas Spain Rubén Armañanzas's profile →
Citations per field
00.5×6.5×
Rubén Armañanzas · 1×
Citations per year

Countries citing papers authored by Fei Zhu

Since Specialization
Citations

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

Fields of papers citing papers by Fei Zhu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fei Zhu

This figure shows the co-authorship network connecting the top 25 collaborators of Fei Zhu. A scholar is included among the top collaborators of Fei Zhu 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 Fei Zhu. Fei Zhu 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 2
3 1
4 2
5 5
6 12
7 4
8 5
9 3
10 4
11 15
12 1
13 13
14 15
15 3
16 44
17 3
18
Quasi-Z-source inverter in grid-connected photovoltaic system
3
19
An integrated Optimized Traffic Monitoring System
1
20
Web-based Approach of Unified Identity Authorization
1

About Fei Zhu

Fei Zhu is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Science Applications, having authored 97 papers that have together received 1.7k indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (19 papers), Computational Drug Discovery Methods (15 papers) and Machine Learning in Bioinformatics (11 papers). The work is most often cited by research in Structural Biology (42 citations), Health Informatics (27 citations) and Cellular and Molecular Neuroscience (296 citations). Fei Zhu has collaborated with scholars based in China, United Kingdom and Canada. Frequent co-authors include Quan Liu, Bairong Shen, Fei Ye, Seth G. N. Grant, Noboru H. Komiyama, René Frank, Javier DeFelipe, Wanwipa Vongsangnak, Ruth Benavides‐Piccione and Maksym V. Kopanitsa. Their work appears in journals such as Nature Communications, Neuron and Bioinformatics.

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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