He Ming Yao

1.1k total citations
39 papers, 758 citations indexed

About

He Ming Yao is a scholar working on Electrical and Electronic Engineering, Atomic and Molecular Physics, and Optics and Ocean Engineering. According to data from OpenAlex, He Ming Yao has authored 39 papers receiving a total of 758 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Electrical and Electronic Engineering, 17 papers in Atomic and Molecular Physics, and Optics and 17 papers in Ocean Engineering. Recurrent topics in He Ming Yao's work include Geophysical Methods and Applications (17 papers), Electromagnetic Scattering and Analysis (16 papers) and Microwave Imaging and Scattering Analysis (15 papers). He Ming Yao is often cited by papers focused on Geophysical Methods and Applications (17 papers), Electromagnetic Scattering and Analysis (16 papers) and Microwave Imaging and Scattering Analysis (15 papers). He Ming Yao collaborates with scholars based in Hong Kong, China and United States. He Ming Yao's co-authors include Lijun Jiang, Wei E. I. Sha, Li Jun Jiang, Huan Huan Zhang, Michael K. Ng, Maokun Li, Rui Guo, Yu Zhang, Min Li and Aria Abubakar and has published in prestigious journals such as IEEE Transactions on Geoscience and Remote Sensing, IEEE Access and IEEE Transactions on Microwave Theory and Techniques.

In The Last Decade

He Ming Yao

35 papers receiving 740 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
He Ming Yao Hong Kong 15 302 295 285 197 153 39 758
Tao Shan China 15 142 0.5× 140 0.5× 229 0.8× 113 0.6× 169 1.1× 40 651
Martina T. Bevacqua Italy 18 631 2.1× 373 1.3× 205 0.7× 90 0.5× 114 0.7× 86 813
İbrahim Akduman Türkiye 20 876 2.9× 371 1.3× 397 1.4× 209 1.1× 265 1.7× 110 1.2k
Norbert Geng United States 15 280 0.9× 476 1.6× 351 1.2× 389 2.0× 197 1.3× 32 866
Li Yi Japan 15 135 0.4× 130 0.4× 329 1.2× 98 0.5× 100 0.7× 83 599
Yu Zhong Singapore 20 933 3.1× 626 2.1× 264 0.9× 340 1.7× 111 0.7× 94 1.3k
Zhongmin Wang China 15 194 0.6× 91 0.3× 375 1.3× 135 0.7× 154 1.0× 32 615
Li Xu China 15 747 2.5× 386 1.3× 496 1.7× 268 1.4× 342 2.2× 81 1.3k
R. Gómez Martín Spain 20 224 0.7× 123 0.4× 699 2.5× 453 2.3× 278 1.8× 94 993
Xiuzhu Ye China 17 445 1.5× 308 1.0× 228 0.8× 170 0.9× 212 1.4× 67 755

Countries citing papers authored by He Ming Yao

Since Specialization
Citations

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

Fields of papers citing papers by He Ming Yao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of He Ming Yao

This figure shows the co-authorship network connecting the top 25 collaborators of He Ming Yao. A scholar is included among the top collaborators of He Ming Yao 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 He Ming Yao. He Ming Yao 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.
Yao, He Ming, et al.. (2024). Deep Learning-Based Fast Full-Wave Electromagnetic Forward Solver Using Physics-Induced Loss. IEEE Antennas and Wireless Propagation Letters. 23(9). 2817–2821.
2.
Zhang, Huan Huan, et al.. (2024). 5G Base Station Antenna Array With Heatsink Radome. IEEE Transactions on Antennas and Propagation. 72(3). 2270–2278. 41 indexed citations
3.
Yao, He Ming, Huan Huan Zhang, Lijun Jiang, & Michael K. Ng. (2024). Enhanced Deep Learning Approach for Electromagnetic Forward Modeling of Dielectric Target Within the Wide Frequency Band Using Deep Residual Convolutional Neural Network. IEEE Antennas and Wireless Propagation Letters. 23(6). 1884–1888. 3 indexed citations
4.
Yao, He Ming, Huan Huan Zhang, Lijun Jiang, & Michael K. Ng. (2024). Fast Electromagnetic Inversion Solver Based on Conditional Generative Adversarial Network for High-Contrast and Heterogeneous Scatterers. IEEE Transactions on Antennas and Propagation. 72(4). 3485–3494. 6 indexed citations
5.
Ng, Michael K. & He Ming Yao. (2023). Deep learning based source reconstruction method using asymmetric encoder–decoder structure and physics-induced loss. Journal of Computational and Applied Mathematics. 438. 115503–115503. 3 indexed citations
6.
Zhang, Huan Huan, He Ming Yao, Lijun Jiang, & Michael K. Ng. (2023). Solving Electromagnetic Inverse Scattering Problems in Inhomogeneous Media by Deep Convolutional Encoder–Decoder Structure. IEEE Transactions on Antennas and Propagation. 71(3). 2867–2872. 13 indexed citations
7.
Zhang, Huan Huan, et al.. (2023). Deep Long Short-Term Memory Networks-Based Solving Method for the FDTD Method: 2-D Case. IEEE Microwave and Wireless Technology Letters. 33(5). 499–502. 14 indexed citations
8.
Zhang, Huan Huan, He Ming Yao, Lijun Jiang, & Michael K. Ng. (2022). Fast Full-Wave Electromagnetic Forward Solver Based on Deep Conditional Convolutional Autoencoders. IEEE Antennas and Wireless Propagation Letters. 22(4). 779–783. 6 indexed citations
9.
Zhang, Huan Huan, He Ming Yao, Lijun Jiang, & Michael K. Ng. (2022). Enhanced Two-Step Deep-Learning Approach for Electromagnetic-Inverse-Scattering Problems: Frequency Extrapolation and Scatterer Reconstruction. IEEE Transactions on Antennas and Propagation. 71(2). 1662–1672. 40 indexed citations
10.
Yao, He Ming, Rui Guo, Maokun Li, Lijun Jiang, & Michael K. Ng. (2022). Enhanced Supervised Descent Learning Technique for Electromagnetic Inverse Scattering Problems by the Deep Convolutional Neural Networks. IEEE Transactions on Antennas and Propagation. 70(8). 6195–6206. 23 indexed citations
11.
Guo, Rui, He Ming Yao, Maokun Li, et al.. (2020). Joint Inversion of Audio-Magnetotelluric and Seismic Travel Time Data With Deep Learning Constraint. IEEE Transactions on Geoscience and Remote Sensing. 59(9). 7982–7995. 60 indexed citations
12.
Yao, He Ming & Lijun Jiang. (2020). Enhanced PML Based on the Long Short Term Memory Network for the FDTD Method. IEEE Access. 8. 21028–21035. 24 indexed citations
13.
Zhang, Huan Huan, He Ming Yao, & Li Jun Jiang. (2016). Novel time domain integral equation method hybridized with the macromodels of circuits. 135–138.
14.
Zhang, Huan Huan, Li Jun Jiang, & He Ming Yao. (2016). Embedding the Behavior Macromodel Into TDIE for Transient Field-Circuit Simulations. IEEE Transactions on Antennas and Propagation. 64(7). 3233–3238. 43 indexed citations
15.
Yao, He Ming, et al.. (2016). Machine learning based MoM (ML-MoM) for parasitic capacitance extractions. The HKU Scholars Hub (University of Hong Kong). 171–173. 11 indexed citations
16.
Li, Chunlai, et al.. (2015). Realization of periodical control and synchronization of single-mode laser Haken-Lorenz system with intermittent feedback. Acta Physica Sinica. 64(3). 30504–30504. 1 indexed citations
17.
Zhang, Huan Huan, He Ming Yao, & Li Jun Jiang. (2015). Novel time domain integral equation method hybridized with the macromodels of circuits. 135–138. 13 indexed citations
18.
Yao, He Ming, et al.. (2015). Nonlinearity of digital I/Os and its behaviour modeling. 52. 35–38. 1 indexed citations
19.
Yao, He Ming, et al.. (2002). A Generalized Post-processing Algorithm to Compensate Geometric Errors of Multi-axis NC Machine Tools with Arbitrary Configuration. 1 indexed citations
20.
Yao, He Ming. (2000). A Self-adaptive Learning Algorithm for BP Network. Systems Engineering - Theory & Practice. 1 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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