Boling Yan

701 total citations
18 papers, 519 citations indexed

About

Boling Yan is a scholar working on Mechanical Engineering, Biomedical Engineering and Electrical and Electronic Engineering. According to data from OpenAlex, Boling Yan has authored 18 papers receiving a total of 519 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Mechanical Engineering, 9 papers in Biomedical Engineering and 7 papers in Electrical and Electronic Engineering. Recurrent topics in Boling Yan's work include Advanced machining processes and optimization (13 papers), Advanced Surface Polishing Techniques (9 papers) and Advanced Machining and Optimization Techniques (7 papers). Boling Yan is often cited by papers focused on Advanced machining processes and optimization (13 papers), Advanced Surface Polishing Techniques (9 papers) and Advanced Machining and Optimization Techniques (7 papers). Boling Yan collaborates with scholars based in China and Singapore. Boling Yan's co-authors include Lida Zhu, Lida Zhu, Yichao Dun, Yanpeng Hao, Changfu Liu, Shaoqing Qin, Hao Lü, Shuhao Wang, Hao Lü and Zhichao Yang and has published in prestigious journals such as Mechanical Systems and Signal Processing, The International Journal of Advanced Manufacturing Technology and IEEE Sensors Journal.

In The Last Decade

Boling Yan

17 papers receiving 504 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Boling Yan China	11	466	226	199	153	49	18	519
Zhou-Long Li China	14	576 1.2×	362 1.6×	160 0.8×	243 1.6×	96 2.0×	24	643
Balla Srinivasa Prasad India	14	524 1.1×	161 0.7×	196 1.0×	80 0.5×	42 0.9×	49	577
Xianyin Duan China	14	441 0.9×	203 0.9×	107 0.5×	161 1.1×	99 2.0×	41	513
Deniz Aslan Canada	8	525 1.1×	257 1.1×	222 1.1×	207 1.4×	55 1.1×	9	577
Johanna Senatore France	13	449 1.0×	199 0.9×	127 0.6×	144 0.9×	138 2.8×	21	497
Farbod Akhavan Niaki United States	13	387 0.8×	134 0.6×	210 1.1×	218 1.4×	45 0.9×	22	497
Paweł Twardowski Poland	12	650 1.4×	268 1.2×	267 1.3×	205 1.3×	55 1.1×	43	699
Iwao YAMAJI Japan	12	431 0.9×	176 0.8×	70 0.4×	111 0.7×	79 1.6×	46	487
Brian S. Dutterer United States	12	650 1.4×	545 2.4×	246 1.2×	176 1.2×	61 1.2×	26	732

Countries citing papers authored by Boling Yan

Since Specialization

Citations

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

Fields of papers citing papers by Boling Yan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Boling Yan

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

All Works

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18 of 18 papers shown

Yan, Boling, et al.. (2025). Investigation on the five-axis stability prediction of rigid and flexible workpiece. Journal of Manufacturing Processes. 141. 132–154.

Lü, Hao, Lida Zhu, Pengsheng Xue, et al.. (2024). Ultrasonic machining response and improvement mechanism for differentiated bio-CoCrMo alloys manufactured by directed energy deposition. Journal of Material Science and Technology. 193. 226–243. 5 indexed citations

Liu, Changfu, et al.. (2024). Hybrid Data Augmentation Combining Screening-Based MCGAN and Manual Transformation for Few-Shot Tool Wear State Recognition. IEEE Sensors Journal. 24(8). 12186–12196. 9 indexed citations

Zhu, Lida, et al.. (2024). On-machine inspection and compensation for thin-walled parts with sculptured surface considering cutting vibration and probe posture. International Journal of Extreme Manufacturing. 6(6). 65602–65602. 10 indexed citations

Zhu, Lida, Yanpeng Hao, Shaoqing Qin, et al.. (2024). On-machine measurement and compensation of thin-walled surface. International Journal of Mechanical Sciences. 271. 109308–109308. 18 indexed citations

Lü, Hao, Lida Zhu, Shuhao Wang, et al.. (2023). The machinability and anisotropy of bio-CoCrMo manufactured by directed energy deposition in ultrasonic vibration assisted drilling. Journal of Materials Research and Technology. 26. 1238–1259. 8 indexed citations

Yang, Zhichao, Lida Zhu, Yichao Dun, et al.. (2023). In-situ monitoring of the melt pool dynamics in ultrasound-assisted metal 3D printing using machine learning. Virtual and Physical Prototyping. 18(1). 22 indexed citations

Yan, Boling, et al.. (2023). Identification of milling information and cutter-workpiece engagement in five-axis finishing of turbine blades based on NURBS and NC codes. Journal of Manufacturing Processes. 107. 43–56. 8 indexed citations

Yan, Boling, Yanpeng Hao, Lida Zhu, & Changfu Liu. (2022). Towards high milling accuracy of turbine blades: A review. Mechanical Systems and Signal Processing. 170. 108727–108727. 74 indexed citations

10.

Hao, Yanpeng, et al.. (2022). Milling chatter detection with WPD and power entropy for Ti-6Al-4V thin-walled parts based on multi-source signals fusion. Mechanical Systems and Signal Processing. 177. 109225–109225. 59 indexed citations

11.

Hao, Yanpeng, et al.. (2022). Stiffness design and multi-objective optimization of machine tool structure based on biological inspiration. Journal of Vibration and Control. 29(11-12). 2774–2788. 10 indexed citations

12.

Zhu, Lida, et al.. (2021). Inspection of blade profile and machining deviation analysis based on sample points optimization and NURBS knot insertion. Thin-Walled Structures. 162. 107540–107540. 46 indexed citations

13.

Yan, Boling, Lida Zhu, & Yichao Dun. (2021). Tool wear monitoring of TC4 titanium alloy milling process based on multi-channel signal and time-dependent properties by using deep learning. Journal of Manufacturing Systems. 61. 495–508. 68 indexed citations

14.

Lü, Hao, Lida Zhu, Zhichao Yang, et al.. (2021). Research on the generation mechanism and interference of surface texture in ultrasonic vibration assisted milling. International Journal of Mechanical Sciences. 208. 106681–106681. 54 indexed citations

15.

Zhu, Lida, et al.. (2021). Research on the milling stability of thin-walled parts based on the semi-discretization method of improved Runge-Kutta method. The International Journal of Advanced Manufacturing Technology. 115(7-8). 2325–2342. 8 indexed citations

16.

Dun, Yichao, Lida Zhu, Boling Yan, & Shuhao Wang. (2021). A chatter detection method in milling of thin-walled TC4 alloy workpiece based on auto-encoding and hybrid clustering. Mechanical Systems and Signal Processing. 158. 107755–107755. 70 indexed citations

17.

Yan, Boling, Lida Zhu, & Changfu Liu. (2020). Prediction model of peripheral milling surface geometry considering cutting force and vibration. The International Journal of Advanced Manufacturing Technology. 110(5-6). 1429–1443. 20 indexed citations

18.

Yan, Boling & Lida Zhu. (2019). Research on milling stability of thin-walled parts based on improved multi-frequency solution. The International Journal of Advanced Manufacturing Technology. 102(1-4). 431–441. 30 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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