Weichang Li

1.9k total citations · 1 hit paper
94 papers, 1.4k citations indexed

About

Weichang Li is a scholar working on Geophysics, Ocean Engineering and Artificial Intelligence. According to data from OpenAlex, Weichang Li has authored 94 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Geophysics, 35 papers in Ocean Engineering and 19 papers in Artificial Intelligence. Recurrent topics in Weichang Li's work include Seismic Imaging and Inversion Techniques (37 papers), Seismic Waves and Analysis (22 papers) and Drilling and Well Engineering (12 papers). Weichang Li is often cited by papers focused on Seismic Imaging and Inversion Techniques (37 papers), Seismic Waves and Analysis (22 papers) and Drilling and Well Engineering (12 papers). Weichang Li collaborates with scholars based in United States, Saudi Arabia and China. Weichang Li's co-authors include James C. Preisig, Daniele Colombo, Mingliang Liu, Michael Jervis, Jerome H. Milgram, Adam K. Usadi, Niranjan Subrahmanya, Erşan Türkoğlu, Diego Rovetta and Slobodan Vučetić and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Journal of the Acoustical Society of America and Optics Letters.

In The Last Decade

Weichang Li

83 papers receiving 1.4k citations

Hit Papers

Estimation of Rapidly Time-Varying Sparse Channels 2007 2026 2013 2019 2007 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Estimation of Rapidly Time-Varying Sparse Channels
    2007 371 citations Weichang Li et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Weichang Li United States 19 565 363 309 260 220 94 1.4k
Fabio Dovis Italy 26 161 0.3× 141 0.4× 1.3k 4.1× 605 2.3× 370 1.7× 282 3.2k
James Collins Austria 8 290 0.5× 193 0.5× 570 1.8× 145 0.6× 398 1.8× 12 1.8k
M. Elizabeth Cannon Canada 27 245 0.4× 58 0.2× 754 2.4× 482 1.9× 688 3.1× 159 2.8k
Omar M. Saad Egypt 27 491 0.9× 1.3k 3.5× 261 0.8× 794 3.1× 34 0.2× 144 2.1k
Liuqing Yang China 18 387 0.7× 599 1.7× 267 0.9× 247 0.9× 22 0.1× 72 1.2k
Jingnan Liu China 19 67 0.1× 248 0.7× 149 0.5× 248 1.0× 246 1.1× 88 1.5k
David P. Williams United States 22 526 0.9× 84 0.2× 198 0.6× 249 1.0× 578 2.6× 85 1.3k
Christian Tiberius Netherlands 28 152 0.3× 89 0.2× 525 1.7× 241 0.9× 1.2k 5.3× 113 2.5k
Sam Pullen United States 28 77 0.1× 221 0.6× 386 1.2× 334 1.3× 718 3.3× 185 2.6k
Xiaolong Chen China 28 298 0.5× 21 0.1× 381 1.2× 269 1.0× 487 2.2× 175 2.6k

Countries citing papers authored by Weichang Li

Since Specialization
Citations

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

Fields of papers citing papers by Weichang Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Weichang Li

This figure shows the co-authorship network connecting the top 25 collaborators of Weichang Li. A scholar is included among the top collaborators of Weichang Li 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 Weichang Li. Weichang Li 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.
Kazei, Vladimir, et al.. (2024). Understanding 3D seismic data visualization with C++, OpenGL and GLSL. Computers & Geosciences. 191. 105681–105681.
2.
Zhang, Qie, Vladimir Kazei, & Weichang Li. (2024). SeisRAFT: A recurrent deep learning network for 4D seismic registration and CO2 storage monitoring. The Leading Edge. 43(8). 554–562.
3.
Pham, Nam, et al.. (2024). Predicting missing sonic logs with seismic constraint. Geophysics. 89(3). D149–D157. 1 indexed citations
4.
Huang, Guoxing, et al.. (2024). A convolutional neural network–back propagation based three-layer combined forecasting method for spare part demand. RAIRO. Operations research. 58(5). 4181–4195. 1 indexed citations
5.
Li, Weichang, et al.. (2023). Is attention all geosciences need? Advancing quantitative petrography with attention-based deep learning. Computers & Geosciences. 181. 105466–105466. 7 indexed citations
6.
7.
Di, Haibin, et al.. (2023). Latest advancements in machine learning for geophysics — Introduction. Geophysics. 89(1). WAi–WAii. 2 indexed citations
8.
Jin, Ge, Vladimir Kazei, Ariel Lellouch, et al.. (2023). Distributed acoustic sensing in geophysics — Introduction. Geophysics. 88(6). WCi–WCii. 1 indexed citations
9.
Ma, Yong, et al.. (2023). Imaging distributed acoustic sensing-to-geophone conversion data: A field application to CO2 sequestration data. Interpretation. 11(2). SB1–SB10. 4 indexed citations
10.
Kazei, Vladimir, et al.. (2023). Diffusion Model for DAS-VSP Data Denoising. Sensors. 23(20). 8619–8619. 11 indexed citations
11.
Colombo, Daniele, Erşan Türkoğlu, Weichang Li, & Diego Rovetta. (2021). Coupled physics-deep learning inversion. Computers & Geosciences. 157. 104917–104917. 18 indexed citations
12.
Pham, Nam & Weichang Li. (2021). Physics-constrained deep learning for ground roll attenuation. Geophysics. 87(1). V15–V27. 28 indexed citations
13.
Zhu, Zhaopeng, et al.. (2021). Intelligent Prediction of Settling Velocity for Arbitrary Shape Particles in Vertical Fractures. 1 indexed citations
14.
Li, Weichang, Wenyi Hu, & Aria Abubakar. (2020). Machine learning and data analytics for geoscience applications — Introduction. Geophysics. 85(4). WAi–WAii. 8 indexed citations
15.
Liu, Mingliang, et al.. (2020). Seismic facies classification using supervised convolutional neural networks and semisupervised generative adversarial networks. Geophysics. 85(4). O47–O58. 104 indexed citations
16.
Bianco, Michael J., Peter Gerstoft, James Traer, et al.. (2019). Machine learning in acoustics: a review.. arXiv (Cornell University). 3 indexed citations
17.
Colombo, Daniele, et al.. (2019). Deep-learning electromagnetic monitoring coupled to fluid flow simulators. Geophysics. 85(4). WA1–WA12. 34 indexed citations
18.
Qin, Zhiwei, Weichang Li, & Firdaus Janoos. (2014). Sparse Reinforcement Learning via Convex Optimization. International Conference on Machine Learning. 424–432. 13 indexed citations
19.
Janoos, Firdaus, Weichang Li, Niranjan Subrahmanya, I Mórocz, & William M. Wells. (2012). Identification of Recurrent Patterns in the Activation of Brain Networks. Neural Information Processing Systems. 25. 674–682. 1 indexed citations
20.
Liu, Cheng, Zhaohua Wang, Weichang Li, et al.. (2010). Contrast enhancement in a Ti:sapphire chirped-pulse amplification laser system with a noncollinear femtosecond optical-parametric amplifier. Optics Letters. 35(18). 3096–3096. 32 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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