Wai Sze Yip

1.5k total citations
82 papers, 1.0k citations indexed

About

Wai Sze Yip is a scholar working on Mechanical Engineering, Biomedical Engineering and Electrical and Electronic Engineering. According to data from OpenAlex, Wai Sze Yip has authored 82 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 60 papers in Mechanical Engineering, 44 papers in Biomedical Engineering and 18 papers in Electrical and Electronic Engineering. Recurrent topics in Wai Sze Yip's work include Advanced Surface Polishing Techniques (42 papers), Advanced machining processes and optimization (40 papers) and Advanced Machining and Optimization Techniques (13 papers). Wai Sze Yip is often cited by papers focused on Advanced Surface Polishing Techniques (42 papers), Advanced machining processes and optimization (40 papers) and Advanced Machining and Optimization Techniques (13 papers). Wai Sze Yip collaborates with scholars based in Hong Kong, China and United States. Wai Sze Yip's co-authors include Suet To, Hanheng Du, Zhanwen Sun, Baolong Zhang, Tengfei Yin, Jingzheng Ren, Muhammad Rehan, Zhiwei Zhu, Changlin Liu and Zhiwei Zhu and has published in prestigious journals such as Journal of Cleaner Production, Scientific Reports and Optics Express.

In The Last Decade

Wai Sze Yip

77 papers receiving 979 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Wai Sze Yip Hong Kong 19 700 457 270 180 156 82 1.0k
Akihiko Kubo Japan 15 729 1.0× 444 1.0× 339 1.3× 160 0.9× 252 1.6× 65 1.1k
Ítalo Tomaz Brazil 14 869 1.2× 248 0.5× 431 1.6× 167 0.9× 213 1.4× 16 1.1k
Asish Bandyopadhyay India 20 912 1.3× 225 0.5× 381 1.4× 143 0.8× 178 1.1× 69 1.2k
Davorin Kramar Slovenia 16 872 1.2× 309 0.7× 510 1.9× 173 1.0× 216 1.4× 53 1.0k
Mehmet Alper Sofuoğlu Türkiye 19 568 0.8× 295 0.6× 242 0.9× 107 0.6× 93 0.6× 56 922
Deepak Rajendra Unune India 20 826 1.2× 462 1.0× 597 2.2× 115 0.6× 98 0.6× 56 1.1k
Linlin Wan China 15 437 0.6× 339 0.7× 197 0.7× 74 0.4× 126 0.8× 29 618
Marta Harničárová Czechia 22 622 0.9× 284 0.6× 151 0.6× 265 1.5× 180 1.2× 138 1.3k
João Fernando Gomes de Oliveira Brazil 18 1.0k 1.5× 675 1.5× 472 1.7× 73 0.4× 177 1.1× 58 1.2k
Zhaohui Deng China 24 1.2k 1.7× 840 1.8× 536 2.0× 180 1.0× 293 1.9× 84 1.6k

Countries citing papers authored by Wai Sze Yip

Since Specialization
Citations

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

Fields of papers citing papers by Wai Sze Yip

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wai Sze Yip. 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 Wai Sze Yip. The network helps show where Wai Sze Yip may publish in the future.

Co-authorship network of co-authors of Wai Sze Yip

This figure shows the co-authorship network connecting the top 25 collaborators of Wai Sze Yip. A scholar is included among the top collaborators of Wai Sze Yip 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 Wai Sze Yip. Wai Sze Yip 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
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Zhang, Baolong, Muhammad Rehan, Chi Ho Wong, et al.. (2025). Exploring the Application of the Internet of Things in Precision Machining by Comparative Text Mining. Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery. 15(3).
4.
Xu, Zhicheng, et al.. (2024). Technological life-cycle analysis of ultra-precision machining technology: Forecasting perspective directions and tracking the critical transitions with evolution. Advanced Engineering Informatics. 62. 102805–102805. 12 indexed citations
5.
Sun, Zhanwen, et al.. (2024). Investigation of rotational magnetic field assisted hot filament chemical vapor deposition for diamond film growth. Surface and Coatings Technology. 495. 131588–131588. 2 indexed citations
6.
To, Suet, Muhammad Rehan, Jingjing Wu, et al.. (2024). Investigation and formulation of cobalt content of ultra-thin diamond blades and dicing performance manufactured by fused deposition modeling and sintering (FDMS). International Journal of Refractory Metals and Hard Materials. 121. 106663–106663. 2 indexed citations
7.
Xu, Zhicheng, et al.. (2024). A review: Insight into smart and sustainable ultra-precision machining augmented by intelligent IoT. Journal of Manufacturing Systems. 74. 233–251. 17 indexed citations
8.
Liu, Changlin, Jinyang Ke, Tengfei Yin, et al.. (2024). Cutting mechanism of reaction-bonded silicon carbide in laser-assisted ultra-precision machining. International Journal of Machine Tools and Manufacture. 203. 104219–104219. 29 indexed citations
9.
Tan, Yi, et al.. (2024). Subsurface damage and brittle fracture suppression of monocrystalline germanium in ultra-precision machining by multiple ion implantation surface modification. Journal of Materials Processing Technology. 334. 118640–118640. 5 indexed citations
10.
Liu, Yue, Tengfei Yin, Zhanwen Sun, et al.. (2024). Magnetic and ultrasonic vibration dual-field assisted ultra-precision diamond cutting of high-entropy alloys. International Journal of Machine Tools and Manufacture. 202. 104208–104208. 23 indexed citations
11.
Sun, Zhanwen, et al.. (2024). Fabrication of diamond film under low methane concentration by hot filament chemical vapor deposition with magnetic field assistance. Surface and Coatings Technology. 483. 130802–130802. 6 indexed citations
12.
Yip, Wai Sze, et al.. (2024). Intelligent Contour Error Compensation of Ultraprecision Machining Using Hybrid Mechanism-Data-Driven Model Assisted With IoT Framework. IEEE Transactions on Industrial Informatics. 20(10). 11815–11824. 5 indexed citations
13.
Zhang, Baolong, et al.. (2024). Sustainability assessment during machining processes: Evidence from the econ-environmental modelling. Journal of Cleaner Production. 448. 141612–141612. 14 indexed citations
14.
Rehan, Muhammad, et al.. (2024). Microstructure and machinability of selective laser melted titanium alloy in micro-milling. Journal of Materials Research and Technology. 33. 8491–8502. 9 indexed citations
15.
Yip, Wai Sze, et al.. (2023). A novel magnetic field assisted diamond turning of Ti-6Al-4 V alloy for sustainable ultra-precision machining. Materials Today Communications. 35. 105829–105829. 18 indexed citations
16.
Li, Denghui, Wai Sze Yip, Hongrui Cao, et al.. (2023). Chatter suppression in diamond turning using magnetic field assistance. Journal of Materials Processing Technology. 321. 118150–118150. 12 indexed citations
17.
Yip, Wai Sze, et al.. (2021). Thematic analysis of sustainable ultra-precision machining by using text mining and unsupervised learning method. Journal of Manufacturing Systems. 62. 218–233. 22 indexed citations
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Yip, Wai Sze, et al.. (2020). Social network analysis for optimal machining conditions in ultra-precision manufacturing. Journal of Manufacturing Systems. 56. 93–103. 23 indexed citations
20.
Ji, Renjie, Liu Y, Suet To, et al.. (2018). Efficient fabrication of gradient nanostructure layer on surface of commercial pure copper by coupling electric pulse and ultrasonics treatment. Journal of Alloys and Compounds. 764. 51–61. 24 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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