Long Jin

349 papers receiving 10.2k citations

Long Jin's Hit Papers

A Momentum Recurrent Neural Network for Sparse Motion Planning of Redundant Manipulators With Majorization-Minimization 2025 · 30 citations
300+3+6Years since publication100200300

Peers

Long Jin
Comparison fields: 5 of 152
  • Numerical Analysis 1k
  • Computational Mathematics 85
  • Artificial Intelligence 4.5k
  • Control and Systems Engineering 3k
  • Computational Theory and Mathematics 1.6k
Replace Lin Xiao with:
Lin Xiao China
Elad Hazan United States
David G. Luenberger United States
Yunong Zhang China
John C. Duchi United States
Brian D. O. Anderson Australia
John B. Moore Australia
Zongben Xu China
Paul Tseng United States
Babak Hassibi United States
Long Jin relative to Lin Xiao China Lin Xiao's profile →
Citations per field
00.5×1.5×
Lin Xiao · 1×
Citations per year

Countries citing papers authored by Long Jin

Since Specialization
Citations

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

Fields of papers citing papers by Long Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 384 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Manipulability Optimization of Redundant Manipulators Using Dynamic Neural Networks
Hit paper breakdown →
2017309
2
Kinematic Control of Redundant Manipulators Using Neural Networks
Hit paper breakdown →
2016266
3 2013254
4 2018245
5 2015236
6 2017220
7 2016218
8 2021200
9 2016199
10 2017198
11 2017185
12 2018177
13 2015165
14
Gradient-Based Differential Neural-Solution to Time-Dependent Nonlinear Optimization
Hit paper breakdown →
2022162
15 2020157
16 2018152
17 2014143
18 2016141
19 2019139
20 2019137

About Long Jin

Long Jin is a scholar working on Artificial Intelligence, Control and Systems Engineering, Numerical Analysis, Computational Theory and Mathematics and Computer Networks and Communications, having authored 384 papers that have together received 10.4k indexed citations. Recurring topics across this work include Neural Networks and Applications (116 papers), Robotic Mechanisms and Dynamics (63 papers), Distributed Control Multi-Agent Systems (29 papers), Hydrological Forecasting Using AI (23 papers), Matrix Theory and Algorithms (21 papers), Optimization and Variational Analysis (20 papers), Advanced Optimization Algorithms Research (20 papers) and Seismic Imaging and Inversion Techniques (17 papers). The work is most often cited by research in Numerical Analysis (1k citations), Computational Mathematics (85 citations), Artificial Intelligence (4.5k citations), Control and Systems Engineering (3k citations) and Computational Theory and Mathematics (1.6k citations). Long Jin has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Shuai Li, Yunong Zhang, Xin Luo, Mei Liu, Bolin Liao, Zhijun Zhang, Lin Xiao, Zhengtai Xie, Zhongbo Sun and Xiuchun Xiao. Their work appears in journals such as Neurocomputing, IEEE Transactions on Systems Man and Cybernetics Systems, IEEE Transactions on Industrial Informatics, IEEE Transactions on Industrial Electronics and IEEE Transactions on Neural Networks and Learning 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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