Bing Yu

1.4k total citations · 1 hit paper
9 papers, 848 citations indexed

About

Bing Yu is a scholar working on Instrumentation, Electrical and Electronic Engineering and Ophthalmology. According to data from OpenAlex, Bing Yu has authored 9 papers receiving a total of 848 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Instrumentation, 5 papers in Electrical and Electronic Engineering and 3 papers in Ophthalmology. Recurrent topics in Bing Yu's work include Advanced Optical Sensing Technologies (5 papers), Optical Systems and Laser Technology (3 papers) and Ocular and Laser Science Research (3 papers). Bing Yu is often cited by papers focused on Advanced Optical Sensing Technologies (5 papers), Optical Systems and Laser Technology (3 papers) and Ocular and Laser Science Research (3 papers). Bing Yu collaborates with scholars based in China and United States. Bing Yu's co-authors include E Weinan, Hongru Yang, Lei Wu, Xiaopeng Wang, Gaoping Li, Bin Yang, Yuan Liang, Chao Chen, Bo Zhang and Rui Zhang and has published in prestigious journals such as IEEE Sensors Journal, Applied Optics and National Remote Sensing Bulletin.

In The Last Decade

Bing Yu

8 papers receiving 812 citations

Hit Papers

align trajectories

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.

The Deep Ritz Method: A Deep Learning-Based Numerical Algorithm for Solving Variational Problems

2018 810 citations E Weinan, Bing Yu Communications in Mathematics and Statistics profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Bing Yu China	4	655	293	165	160	119	9	848
Jens Berg Sweden	9	419 0.6×	279 1.0×	99 0.6×	95 0.6×	84 0.7×	11	656
Hanwen Wang China	5	604 0.9×	262 0.9×	84 0.5×	192 1.2×	79 0.7×	11	908
Deep Ray United States	11	448 0.7×	370 1.3×	50 0.3×	99 0.6×	122 1.0×	24	727
Youngsoo Choi United States	16	581 0.9×	317 1.1×	67 0.4×	71 0.4×	229 1.9×	35	809
Hayden Schaeffer United States	12	584 0.9×	259 0.9×	43 0.3×	230 1.4×	227 1.9×	39	987
Matthew J. Zahr United States	17	775 1.2×	570 1.9×	104 0.6×	67 0.4×	343 2.9×	45	1.1k
Daniele Venturi United States	17	474 0.7×	273 0.9×	43 0.3×	91 0.6×	399 3.4×	40	952
Roberto Molinaro Switzerland	9	347 0.5×	177 0.6×	67 0.4×	103 0.6×	47 0.4×	10	539
Federico Negri Switzerland	8	766 1.2×	497 1.7×	131 0.8×	35 0.2×	321 2.7×	11	989
Julien Cortial France	8	820 1.3×	499 1.7×	115 0.7×	33 0.2×	401 3.4×	16	1.1k

Countries citing papers authored by Bing Yu

Since Specialization

Citations

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

Fields of papers citing papers by Bing Yu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bing Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Bing Yu. A scholar is included among the top collaborators of Bing Yu 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 Bing Yu. Bing Yu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

9 of 9 papers shown

1.

Yu, Bing, Junfeng Jiang, Lei Wang, et al.. (2025). Different Packaging Methods With Whispering Gallery Mode Resonators for Sensing: A Review. IEEE Sensors Journal. 25(11). 18608–18623.

2.

Tan, Hao, et al.. (2018). Multi-Objective Distribution Network Reconfiguration Based on Deep Learning Algorithm. 1–4. 2 indexed citations

3.

Li, Guangyu, et al.. (2018). Land subsidence detection and analysis over Beijing-Tianjin-Hebei area based on Sentinel-1A TS-DInSAR. National Remote Sensing Bulletin. 22(4). 633–646. 7 indexed citations

4.

Niu, Lihong, et al.. (2018). Target 3-D reconstruction of streak tube imaging lidar based on Gaussian fitting. 104–104. 1 indexed citations

5.

Weinan, E & Bing Yu. (2018). The Deep Ritz Method: A Deep Learning-Based Numerical Algorithm for Solving Variational Problems. Communications in Mathematics and Statistics. 6(1). 1–12. 810 indexed citations breakdown →

6.

Niu, Lihong, et al.. (2017). Research on 3D Imaging Based on Streak Tube Imaging Lidar. DEStech Transactions on Computer Science and Engineering. 2 indexed citations

7.

Qiu, Su, et al.. (2015). The integrated platform of controlling and digital video processing for underwater range-gated laser imaging system. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9522. 95221R–95221R. 1 indexed citations

8.

Wu, Lei, Xiaopeng Wang, Hongru Yang, et al.. (2012). Signal-to-noise performance analysis of streak tube imaging lidar systems II Theoretical analysis and discussion. Applied Optics. 51(36). 8836–8836. 11 indexed citations

9.

Yang, Hongru, Lei Wu, Xiaopeng Wang, et al.. (2012). Signal-to-noise performance analysis of streak tube imaging lidar systems I Cascaded model. Applied Optics. 51(36). 8825–8825. 14 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.

Explore authors with similar magnitude of impact