Lequn Chen

1.9k total citations · 1 hit paper
34 papers, 1.3k citations indexed

About

Lequn Chen is a scholar working on Mechanical Engineering, Automotive Engineering and Industrial and Manufacturing Engineering. According to data from OpenAlex, Lequn Chen has authored 34 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Mechanical Engineering, 16 papers in Automotive Engineering and 15 papers in Industrial and Manufacturing Engineering. Recurrent topics in Lequn Chen's work include Additive Manufacturing Materials and Processes (20 papers), Additive Manufacturing and 3D Printing Technologies (16 papers) and Welding Techniques and Residual Stresses (9 papers). Lequn Chen is often cited by papers focused on Additive Manufacturing Materials and Processes (20 papers), Additive Manufacturing and 3D Printing Technologies (16 papers) and Welding Techniques and Residual Stresses (9 papers). Lequn Chen collaborates with scholars based in Singapore, China and United States. Lequn Chen's co-authors include Seung Ki Moon, Xiling Yao, Luming Shen, Yuejin Tong, In Yee Phang, Tianxi Liu, Guijun Bi, Chaolin Tan, Youxiang Chew and Jinlong Su and has published in prestigious journals such as Composites Science and Technology, Materials Today and Advanced Science.

In The Last Decade

Lequn Chen

34 papers receiving 1.3k citations

Hit Papers

Recent innovations in laser additive manufacturing of tit... 2024 2026 2025 2024 20 40 60
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. Recent innovations in laser additive manufacturing of titanium alloys
    2024 69 citations Jinlong Su, Fulin Jiang 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
Lequn Chen Singapore 17 582 332 261 247 194 34 1.3k
Sébastien Garnier France 20 772 1.3× 196 0.6× 131 0.5× 289 1.2× 159 0.8× 50 1.8k
Dhinakaran Veeman India 19 452 0.8× 326 1.0× 135 0.5× 65 0.3× 210 1.1× 96 1.1k
R. Soundararajan India 18 803 1.4× 293 0.9× 77 0.3× 121 0.5× 100 0.5× 116 1.2k
V. Dhinakaran India 22 931 1.6× 467 1.4× 83 0.3× 99 0.4× 166 0.9× 90 1.7k
S. Kaliappan India 24 543 0.9× 218 0.7× 208 0.8× 75 0.3× 635 3.3× 181 1.7k
Z. Shayfull Malaysia 17 500 0.9× 335 1.0× 82 0.3× 234 0.9× 147 0.8× 130 969
Kazem Fayazbakhsh Canada 19 612 1.1× 535 1.6× 92 0.4× 272 1.1× 115 0.6× 42 1.7k
Shujuan Li China 22 600 1.0× 274 0.8× 130 0.5× 154 0.6× 240 1.2× 120 1.7k
R. Saravanan India 26 990 1.7× 160 0.5× 235 0.9× 51 0.2× 354 1.8× 191 2.0k
S. Ramabalan India 20 629 1.1× 91 0.3× 48 0.2× 207 0.8× 83 0.4× 62 1.2k

Countries citing papers authored by Lequn Chen

Since Specialization
Citations

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

Fields of papers citing papers by Lequn Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lequn Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Lequn Chen. A scholar is included among the top collaborators of Lequn Chen 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 Lequn Chen. Lequn Chen 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.
Su, Jinlong, Lequn Chen, S. Van Petegem, et al.. (2025). Additive manufacturing metallurgy guided machine learning design of versatile alloys. Materials Today. 88. 240–250. 7 indexed citations
2.
Chen, Lequn, et al.. (2025). Audio-visual cross-modality knowledge transfer for machine learning-based in-situ monitoring in laser additive manufacturing. Additive manufacturing. 101. 104692–104692. 7 indexed citations
3.
4.
Chen, Lequn, Guijun Bi, Xiling Yao, et al.. (2024). In-situ process monitoring and adaptive quality enhancement in laser additive manufacturing: A critical review. Journal of Manufacturing Systems. 74. 527–574. 57 indexed citations
5.
Chen, Lequn & Seung Ki Moon. (2024). In-situ defect detection in laser-directed energy deposition with machine learning and multi-sensor fusion. Journal of Mechanical Science and Technology. 38(9). 4477–4484. 10 indexed citations
6.
7.
Chen, Lequn, Xiling Yao, Chaolin Tan, et al.. (2023). In-situ crack and keyhole pore detection in laser directed energy deposition through acoustic signal and deep learning. Additive manufacturing. 69. 103547–103547. 44 indexed citations
8.
Chen, Lequn, Guijun Bi, Xiling Yao, et al.. (2023). Multisensor fusion-based digital twin for localized quality prediction in robotic laser-directed energy deposition. Robotics and Computer-Integrated Manufacturing. 84. 102581–102581. 77 indexed citations
9.
10.
Chen, Lequn, et al.. (2023). Additive Manufacturing for Automotive Industry: Status, Challenges and Future Perspectives. 1431–1436. 5 indexed citations
11.
12.
Tan, Chaolin, Qian Li, Xiling Yao, et al.. (2023). Machine Learning Customized Novel Material for Energy‐Efficient 4D Printing. Advanced Science. 10(10). e2206607–e2206607. 57 indexed citations
13.
Chen, Lequn, Xiling Yao, Kui Liu, Chaolin Tan, & Seung Ki Moon. (2023). MULTISENSOR FUSION-BASED DIGITAL TWIN IN ADDITIVE MANUFACTURING FOR IN-SITU QUALITY MONITORING AND DEFECT CORRECTION. Proceedings of the Design Society. 3. 2755–2764. 27 indexed citations
14.
Chen, Lequn, et al.. (2023). Key Enabling Technologies for Smart Factory in Automotive Industry: Status and Applications. 1(1). 93–105. 41 indexed citations
15.
Moon, Seung Ki, et al.. (2023). A novel quality inspection method for aerosol jet printed sensors through infrared imaging and machine learning. CIRP Annals. 72(1). 165–168. 4 indexed citations
16.
Chen, Lequn, Xiling Yao, & Seung Ki Moon. (2022). In-situ acoustic monitoring of direct energy deposition process with deep learning-assisted signal denoising. Materials Today Proceedings. 70. 136–142. 21 indexed citations
17.
Chen, Lequn, et al.. (2022). In-situ Melt Pool Monitoring of Laser Aided Additive Manufacturing using Infrared Thermal Imaging. 2022 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). 10 indexed citations
18.
Chen, Lequn, Xiling Yao, Chaolin Tan, et al.. (2022). In-Situ Crack and Keyhole Pore Detection in Laser Directed Energy Deposition Through Acoustic Signal and Deep Learning. SSRN Electronic Journal. 25 indexed citations
19.
Su, Jinlong, Chaolin Tan, Fern Lan Ng, et al.. (2022). Additive manufacturing of novel heterostructured martensite-austenite dual-phase steel through in-situ alloying. Materials Today Communications. 33. 104724–104724. 13 indexed citations
20.
Chen, Lequn, et al.. (2019). A vision for autonomous blockchains backed by secure hardware. 1–6. 3 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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