Heng Liu

5.0k total citations · 2 hit papers
266 papers, 3.5k citations indexed

About

Heng Liu is a scholar working on Artificial Intelligence, Computer Networks and Communications and Control and Systems Engineering. According to data from OpenAlex, Heng Liu has authored 266 papers receiving a total of 3.5k indexed citations (citations by other indexed papers that have themselves been cited), including 85 papers in Artificial Intelligence, 78 papers in Computer Networks and Communications and 64 papers in Control and Systems Engineering. Recurrent topics in Heng Liu's work include Neural Networks Stability and Synchronization (57 papers), Chaos control and synchronization (45 papers) and Neural Networks and Applications (45 papers). Heng Liu is often cited by papers focused on Neural Networks Stability and Synchronization (57 papers), Chaos control and synchronization (45 papers) and Neural Networks and Applications (45 papers). Heng Liu collaborates with scholars based in China, United States and South Korea. Heng Liu's co-authors include Sheng-Gang Li, Jinde Cao, Yongping Pan, Hongxing Wang, Ye Chen, Guanjun Li, Yan Zhou, Qian Wang, Chengdai Huang and Richard A. Davis and has published in prestigious journals such as Journal of Biological Chemistry, SHILAP Revista de lepidopterología and Journal of the American Statistical Association.

In The Last Decade

Heng Liu

241 papers receiving 3.4k citations

Hit Papers

Adaptive Fuzzy Backstepping Control of Fractional-Order N... 2017 2026 2020 2023 2017 2022 50 100 150 200 250

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Heng Liu China 30 1.3k 998 976 850 296 266 3.5k
Fawaz E. Alsaadi Saudi Arabia 33 648 0.5× 834 0.8× 1.1k 1.1× 937 1.1× 363 1.2× 138 3.6k
Feiqi Deng China 38 3.0k 2.2× 613 0.6× 2.7k 2.8× 763 0.9× 483 1.6× 413 5.5k
Peter E. Caines Canada 34 2.6k 1.9× 717 0.7× 716 0.7× 603 0.7× 462 1.6× 294 6.5k
Giuseppe De Nicolao Italy 46 3.5k 2.7× 827 0.8× 408 0.4× 281 0.3× 331 1.1× 277 8.3k
Jeff S. Shamma United States 39 4.8k 3.6× 971 1.0× 2.1k 2.2× 543 0.6× 946 3.2× 201 8.7k
Qingling Zhang China 42 5.9k 4.4× 625 0.6× 2.8k 2.9× 695 0.8× 366 1.2× 403 7.4k
Antonis Papachristodoulou United Kingdom 37 2.6k 1.9× 355 0.4× 1.4k 1.4× 395 0.5× 589 2.0× 218 5.3k
Huaqing Li China 43 1.5k 1.2× 865 0.9× 3.4k 3.5× 520 0.6× 1.2k 3.9× 299 5.9k
Bor‐Sen Chen Taiwan 40 4.6k 3.4× 1.5k 1.5× 1.7k 1.8× 510 0.6× 891 3.0× 371 8.0k
Y. C. Ho United States 29 929 0.7× 958 1.0× 726 0.7× 413 0.5× 581 2.0× 120 4.5k

Countries citing papers authored by Heng Liu

Since Specialization
Citations

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

Fields of papers citing papers by Heng Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Heng Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Heng Liu. A scholar is included among the top collaborators of Heng Liu 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 Heng Liu. Heng Liu 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.
Huang, Chengdai, et al.. (2025). Global Mittag-Leffler synchronization of discontinuous memristor-based fractional-order fuzzy inertial neural networks with mixed delays. Neurocomputing. 626. 129475–129475. 2 indexed citations
2.
Liu, Heng, et al.. (2025). Revenue effects of ambiguity in multi-unit auctions. Journal of Economic Theory. 225. 105996–105996. 1 indexed citations
3.
Xiang, Wei, Heng Liu, & Jinde Cao. (2024). Composite learning prescribed performance control of strict-feedback nonlinear systems with mismatched parametric uncertainties. Journal of the Franklin Institute. 361(16). 107161–107161.
4.
Huang, Chengdai, et al.. (2024). Extractions of bifurcation in fractional-order recurrent neural networks under neurons arbitrariness. Physica D Nonlinear Phenomena. 468. 134279–134279.
5.
Xu, Weidong, et al.. (2024). Optically compatible infrared camouflage performance of ITO ink. RSC Advances. 14(25). 17355–17363. 2 indexed citations
6.
Huang, Chengdai, et al.. (2024). Dynamical bifurcations in a delayed fractional‐order neural network involving neutral terms. Mathematical Methods in the Applied Sciences. 48(2). 2253–2266.
7.
Li, Sheng-Gang, et al.. (2024). Observer-based fuzzy event-triggered control for state constrained MIMO fractional-order systems. Expert Systems with Applications. 256. 124915–124915. 11 indexed citations
8.
Cao, Jinde, et al.. (2024). Delay-dependent parameters bifurcation in a fractional neural network via geometric methods. Applied Mathematics and Computation. 478. 128812–128812. 3 indexed citations
9.
Huang, Chengdai, et al.. (2024). Delay-dependent bifurcation conditions in a fractional-order inertial BAM neural network. Chaos Solitons & Fractals. 185. 115106–115106. 6 indexed citations
10.
Cao, Jinde, et al.. (2024). Adaptive Neural Network Optimal Backstepping Control of Strict Feedback Nonlinear Systems via Reinforcement Learning. IEEE Transactions on Emerging Topics in Computational Intelligence. 9(1). 832–847. 1 indexed citations
11.
Huang, Chengdai, et al.. (2023). Bifurcation analysis of a fractional-order Cohen–Grossberg neural network with three delays. Chinese Journal of Physics. 88. 360–379. 6 indexed citations
12.
Liu, Heng, et al.. (2023). Dissipativity and synchronization of fractional-order output-coupled neural networks with multiple adaptive coupling weights. Mathematics and Computers in Simulation. 215. 306–322. 4 indexed citations
13.
Liu, Heng, et al.. (2023). Identification of interdependent values in sequential first-price auctions. International Journal of Industrial Organization. 91. 103033–103033.
14.
Korovin, Iakov, et al.. (2023). Distributed adaptive neural network consensus control of fractional-order multi-agent systems with unknown control directions. Information Sciences. 655. 119871–119871. 14 indexed citations
15.
Liu, Heng, Cheng Xu, Bill H. Diplas, et al.. (2023). Cancer-associated SMARCAL1 loss-of-function mutations promote alternative lengthening of telomeres and tumorigenesis in telomerase-negative glioblastoma cells. Neuro-Oncology. 25(9). 1563–1575. 11 indexed citations
16.
Xue, Guangming, et al.. (2023). Event-triggered finite-time fuzzy control approach for fractional-order nonlinear chaotic systems with input delay. Chaos Solitons & Fractals. 175. 114036–114036. 14 indexed citations
17.
Xue, Guangming, et al.. (2023). Finite-time sliding mode fault-tolerant neural network control for nonstrict-feedback nonlinear systems. Nonlinear Dynamics. 111(18). 17205–17227. 14 indexed citations
18.
Fang, Zhiming, et al.. (2023). Stabilization of delayed fractional‐order T‐S fuzzy systems with input saturations and system uncertainties. Asian Journal of Control. 26(1). 246–264. 5 indexed citations
19.

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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