Jinglu Hu

633 citations
52 papers · 427 indexed · h-index 11

Jinglu Hu

49 papers receiving 385 citations

Peers

Jinglu Hu
Comparison fields: 5 of 55
  • Artificial Intelligence 276
  • Control and Systems Engineering 148
  • Management Science and Operations Research 63
  • Computational Theory and Mathematics 42
  • Building and Construction 33
Replace Cheng-Yu Hsu with:
Cheng-Yu Hsu Taiwan
Kotaro Hirasawa Japan
Nevena Lazic United States
Shounak Roychowdhury United States
Lev Kazakovtsev Russia
Gintaras Palubeckis Lithuania
Jui-Fang Chang Taiwan
Kazi Shah Nawaz Ripon Norway
Koji Nonobe Japan
Guangzhou Zeng China
Jinglu Hu relative to Cheng-Yu Hsu Taiwan Cheng-Yu Hsu's profile →
Citations per field
00.5×3.8×
Cheng-Yu Hsu · 1×
Citations per year

Countries citing papers authored by Jinglu Hu

Since Specialization
Citations

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

Fields of papers citing papers by Jinglu Hu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20221
3 20223
4 20102
5 20081
6 20071
7 20071
8 20061
9 200512
10 20045
11 20031
12 20030
13 200320
14 20021
15 20021
16 20014
17 19991
18 199813
19 199830
20 199837

About Jinglu Hu

Jinglu Hu is a scholar working on Artificial Intelligence, Signal Processing and Control and Systems Engineering, having authored 52 papers that have together received 427 indexed citations. Recurring topics across this work include Neural Networks and Applications (15 papers), Evolutionary Algorithms and Applications (12 papers), Metaheuristic Optimization Algorithms Research (12 papers), Fault Detection and Control Systems (5 papers), Face and Expression Recognition (5 papers), Reinforcement Learning in Robotics (4 papers), Stock Market Forecasting Methods (4 papers) and Gene Regulatory Network Analysis (4 papers). The work is most often cited by research in Artificial Intelligence (276 citations), Control and Systems Engineering (148 citations) and Management Science and Operations Research (63 citations). Jinglu Hu has collaborated with scholars based in Japan, China and United States. Frequent co-authors include Kotaro Hirasawa, Junichi Murata, Yu Lu, Zhou Jin, Sandor Markon, Toru EGUCHI, Shingo Mabu, Takashi Yamashita, M. Ohbayashi and Shinji Sakai. Their work appears in journals such as IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics), Anaesthesia and Intensive Care, IET Computer Vision, Journal of Advanced Computational Intelligence and Intelligent Informatics and IEEJ Transactions on Electronics Information and Systems.

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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