Xing He

3.9k total citations
152 papers, 3.0k citations indexed

About

Xing He is a scholar working on Computer Networks and Communications, Artificial Intelligence and Electrical and Electronic Engineering. According to data from OpenAlex, Xing He has authored 152 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 53 papers in Computer Networks and Communications, 44 papers in Artificial Intelligence and 40 papers in Electrical and Electronic Engineering. Recurrent topics in Xing He's work include Neural Networks Stability and Synchronization (37 papers), Sparse and Compressive Sensing Techniques (32 papers) and Neural Networks and Applications (29 papers). Xing He is often cited by papers focused on Neural Networks Stability and Synchronization (37 papers), Sparse and Compressive Sensing Techniques (32 papers) and Neural Networks and Applications (29 papers). Xing He collaborates with scholars based in China, Qatar and Australia. Xing He's co-authors include Tingwen Huang, Chuandong Li, Chaojie Li, Junjian Huang, Junzhi Yu, Yushu Zhang, Xinghuo Yu, You Zhao, Leo Yu Zhang and Yonglu Shu and has published in prestigious journals such as IEEE Transactions on Automatic Control, IEEE Transactions on Industrial Electronics and Applied Energy.

In The Last Decade

Xing He

145 papers receiving 3.0k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Xing He China 28 1.3k 921 745 677 599 152 3.0k
Qingshan Liu China 30 1.8k 1.4× 717 0.8× 1.0k 1.4× 1.1k 1.7× 171 0.3× 118 3.6k
Shuai Song China 36 1.4k 1.1× 560 0.6× 1.9k 2.6× 753 1.1× 567 0.9× 131 3.6k
Ruggero Carli Italy 29 2.5k 2.0× 994 1.1× 1.1k 1.5× 619 0.9× 113 0.2× 166 3.6k
Eloy García United States 27 1.8k 1.4× 321 0.3× 1.5k 2.0× 273 0.4× 273 0.5× 124 3.3k
Wee Peng Tay Singapore 26 1.2k 0.9× 983 1.1× 377 0.5× 867 1.3× 535 0.9× 189 2.8k
Jianlong Qiu China 33 2.2k 1.7× 662 0.7× 1.3k 1.7× 527 0.8× 1.0k 1.7× 233 3.8k
Gonzalo Mateos United States 25 1.2k 0.9× 445 0.5× 163 0.2× 1.1k 1.6× 337 0.6× 97 3.0k
Lei Zou China 38 2.8k 2.2× 774 0.8× 3.3k 4.4× 1.3k 1.8× 208 0.3× 138 5.1k
Riccardo Caponetto Italy 25 518 0.4× 564 0.6× 1.4k 1.8× 562 0.8× 744 1.2× 130 3.2k
Michael M. Zavlanos United States 32 2.8k 2.2× 452 0.5× 642 0.9× 591 0.9× 86 0.1× 125 3.8k

Countries citing papers authored by Xing He

Since Specialization
Citations

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

Fields of papers citing papers by Xing He

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xing He

This figure shows the co-authorship network connecting the top 25 collaborators of Xing He. A scholar is included among the top collaborators of Xing He 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 Xing He. Xing He 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
1.
Zhang, Meng & Xing He. (2024). A continuous-time neurodynamic approach in matrix form for rank minimization. Neural Networks. 172. 106128–106128. 1 indexed citations
2.
He, Xing, et al.. (2024). Distributed continuous-time accelerated neurodynamic approaches for sparse recovery via smooth approximation to L1-minimization. Neural Networks. 172. 106123–106123. 1 indexed citations
3.
He, Xing, et al.. (2024). Distributed Inertial Proximal Neurodynamic Approach for Sparse Recovery on Directed Networks. IEEE Transactions on Systems Man and Cybernetics Systems. 54(10). 6180–6193. 1 indexed citations
4.
He, Xing, et al.. (2024). Fixed-time neural networks with time-invariant and time-varying coefficients for mixed variational inequalities. Information Sciences. 659. 120078–120078. 1 indexed citations
5.
He, Xing, et al.. (2024). Accelerated Primal-Dual Projection Neurodynamic Approach With Time Scaling for Linear and Set Constrained Convex Optimization Problems. IEEE/CAA Journal of Automatica Sinica. 11(6). 1485–1498. 3 indexed citations
6.
He, Xing, et al.. (2023). A fixed-time gradient algorithm for distributed optimization with inequality constraints. Neurocomputing. 532. 106–113. 7 indexed citations
7.
8.
Han, Xin, et al.. (2023). A distributed neurodynamic algorithm for sparse signal reconstruction via ℓ1-minimization. Neurocomputing. 550. 126480–126480. 5 indexed citations
9.
Wu, Jintao, et al.. (2023). Circuit Implementation of Proximal Projection Neural Networks for Composite Optimization Problems. IEEE Transactions on Industrial Electronics. 71(2). 1948–1957. 11 indexed citations
10.
Huang, Junjian, et al.. (2023). Bipartite Synchronization of Signed Lur’e Network via Quantized Control. IEEE Transactions on Circuits & Systems II Express Briefs. 70(7). 2475–2479. 6 indexed citations
11.
Han, Xin, Xing He, Mingliang Zhou, & Tingwen Huang. (2023). Inverse-free distributed neurodynamic optimization algorithms for sparse reconstruction. Signal Processing. 218. 109360–109360. 1 indexed citations
12.
He, Xing, Jun Ji, Kaixin Liu, Zengliang Gao, & Yi Liu. (2019). Soft Sensing of Silicon Content via Bagging Local Semi-Supervised Models. Sensors. 19(17). 3814–3814. 17 indexed citations
13.
Zhao, You, Xing He, Tingwen Huang, Junjian Huang, & Peng Li. (2019). A smoothing neural network for minimization l1-lp in sparse signal reconstruction with measurement noises. Neural Networks. 122. 40–53. 19 indexed citations
14.
He, Xing, You Zhao, & Tingwen Huang. (2019). Optimizing the Dynamic Economic Dispatch Problem by the Distributed Consensus-Based ADMM Approach. IEEE Transactions on Industrial Informatics. 16(5). 3210–3221. 85 indexed citations
15.
Zhao, You, Xing He, Yao Yao, & Junjian Huang. (2019). Plug-in electric vehicle charging management via a distributed neurodynamic algorithm. Applied Soft Computing. 80. 557–566. 25 indexed citations
16.
He, Xing, Junzhi Yu, Tingwen Huang, Chuandong Li, & Chaojie Li. (2018). Average Quasi-Consensus Algorithm for Distributed Constrained Optimization: Impulsive Communication Framework. IEEE Transactions on Cybernetics. 50(1). 351–360. 34 indexed citations
17.
He, Xing, Junzhi Yu, Tingwen Huang, & Chaojie Li. (2018). Distributed Power Management for Dynamic Economic Dispatch in the Multimicrogrids Environment. IEEE Transactions on Control Systems Technology. 27(4). 1651–1658. 52 indexed citations
18.
He, Xing, Daniel W. C. Ho, Tingwen Huang, et al.. (2017). Second-Order Continuous-Time Algorithms for Economic Power Dispatch in Smart Grids. IEEE Transactions on Systems Man and Cybernetics Systems. 48(9). 1482–1492. 136 indexed citations
19.
He, Xing, Tingwen Huang, Junzhi Yu, Chaojie Li, & Yushu Zhang. (2017). A Continuous-Time Algorithm for Distributed Optimization Based on Multiagent Networks. IEEE Transactions on Systems Man and Cybernetics Systems. 49(12). 2700–2709. 52 indexed citations
20.
He, Xing, Chuandong Li, Tingwen Huang, Chaojie Li, & Junjian Huang. (2013). A Recurrent Neural Network for Solving Bilevel Linear Programming Problem. IEEE Transactions on Neural Networks and Learning Systems. 25(4). 824–830. 99 indexed citations

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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