Vincent C. S. Lee

2.7k total citations · 1 hit paper
75 papers, 1.8k citations indexed

About

Vincent C. S. Lee is a scholar working on Artificial Intelligence, Information Systems and Civil and Structural Engineering. According to data from OpenAlex, Vincent C. S. Lee has authored 75 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Artificial Intelligence, 13 papers in Information Systems and 10 papers in Civil and Structural Engineering. Recurrent topics in Vincent C. S. Lee's work include Infrastructure Maintenance and Monitoring (10 papers), Cryptography and Data Security (7 papers) and Privacy-Preserving Technologies in Data (7 papers). Vincent C. S. Lee is often cited by papers focused on Infrastructure Maintenance and Monitoring (10 papers), Cryptography and Data Security (7 papers) and Privacy-Preserving Technologies in Data (7 papers). Vincent C. S. Lee collaborates with scholars based in Australia, China and Singapore. Vincent C. S. Lee's co-authors include Ye Lü, Jianghua Deng, Ling Ding, Xu Yang, Marc Cheong, Jinchao Guan, Jingwei Liu, Xin Wang, Sang Luo and Stephen Lau and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Construction and Building Materials.

In The Last Decade

Vincent C. S. Lee

69 papers receiving 1.7k 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.

Automated pavement crack detection and segmentation based on two-step convolutional neural network

2020 286 citations Vincent C. S. Lee et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Vincent C. S. Lee Australia	19	862	391	248	154	141	75	1.8k
Shang‐Hsien Hsieh Taiwan	26	448 0.5×	174 0.4×	132 0.5×	98 0.6×	143 1.0×	117	1.8k
Weili Fang Australia	26	1.2k 1.4×	544 1.4×	81 0.3×	94 0.6×	335 2.4×	45	3.1k
Asim Karim Pakistan	22	391 0.5×	760 1.9×	61 0.2×	173 1.1×	167 1.2×	72	2.1k
Min Hu China	20	264 0.3×	361 0.9×	46 0.2×	64 0.4×	418 3.0×	74	1.3k
Wenyu Zhang China	15	238 0.3×	201 0.5×	71 0.3×	218 1.4×	108 0.8×	22	1.3k
John Kunz United States	26	188 0.2×	373 1.0×	265 1.1×	171 1.1×	125 0.9×	86	2.4k
Francesco Archetti Italy	19	372 0.4×	334 0.9×	53 0.2×	54 0.4×	73 0.5×	112	1.4k
Hong Liu China	28	435 0.5×	124 0.3×	94 0.4×	165 1.1×	155 1.1×	148	2.4k
Haitao Wu China	19	172 0.2×	204 0.5×	37 0.1×	294 1.9×	83 0.6×	54	1.3k

Countries citing papers authored by Vincent C. S. Lee

Since Specialization

Citations

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

Fields of papers citing papers by Vincent C. S. Lee

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Vincent C. S. Lee. 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 Vincent C. S. Lee. The network helps show where Vincent C. S. Lee may publish in the future.

Co-authorship network of co-authors of Vincent C. S. Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Vincent C. S. Lee. A scholar is included among the top collaborators of Vincent C. S. Lee 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 Vincent C. S. Lee. Vincent C. S. Lee 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:

20 of 20 papers shown

1.

Liu, Feng, et al.. (2025). Dynamic Ensemble Transfer Learning with Multi-view Ultrasonography for Improving Thyroid Cancer Diagnostic Reliability. Journal of Imaging Informatics in Medicine.

2.

Lee, Vincent C. S., et al.. (2025). The Distributed Intelligent Collaboration to AAV-Assisted VEC: Joint Position Optimization and Task Scheduling. IEEE Internet of Things Journal. 12(12). 21473–21487. 2 indexed citations

3.

Obaidat, Mohammad S., et al.. (2024). An Effective Learning Management System for Revealing Student Performance Attributes. 1–8.

4.

Lee, Vincent C. S., et al.. (2024). Optimal service resource management strategy for IoT-based health information system considering value co-creation of users. Industrial Management & Data Systems. 124(3). 1132–1154. 1 indexed citations

5.

Phillipson, Shane N., et al.. (2023). Artificial Neural Networks and the Actiotope Model of Giftedness—Clever Solutions from Complex Environments. Journal of Intelligence. 11(7). 128–128. 6 indexed citations

6.

Zhu, Fengda, Vincent C. S. Lee, Xiaojun Chang, & Xiaodan Liang. (2023). Vision Language Navigation with Knowledge-driven Environmental Dreamer. Monash University Research Portal (Monash University). 1840–1848.

7.

Lee, Vincent C. S., et al.. (2023). Unveiling Thyroid Disease Associations: An Exceptionality-Based Data Mining Technique. SHILAP Revista de lepidopterología. 4(3). 558–572. 2 indexed citations

8.

Liu, Yixin, Kaize Ding, Jianling Wang, et al.. (2023). Learning Strong Graph Neural Networks with Weak Information. arXiv (Cornell University). 1559–1571. 24 indexed citations

9.

Lee, Vincent C. S., et al.. (2023). Compliance Analyses of Australia's Online Household Appliances. 1285–1286. 1 indexed citations

10.

Lee, Vincent C. S., et al.. (2022). A multi-channel deep convolutional neural network for multi-classifying thyroid diseases. Computers in Biology and Medicine. 148. 105961–105961. 15 indexed citations

11.

Aleti, Aldeida, et al.. (2019). Robotic Hierarchical Graph Neurons. A novel implementation of HGN for swarm robotic behaviour control. arXiv (Cornell University). 1 indexed citations

12.

Teo, Sin G., Jianneng Cao, & Vincent C. S. Lee. (2018). DAG: A General Model for Privacy-Preserving Data Mining. IEEE Transactions on Knowledge and Data Engineering. 32(1). 40–53. 17 indexed citations

13.

Cheung, Yen, et al.. (2016). Winning digital citizens: A model and instrument. Monash University Research Portal (Monash University). 336. 1 indexed citations

14.

Cheung, Yen, et al.. (2015). Gov2.0: A service science perspective. Journal of the Association for Information Systems. 160. 4 indexed citations

15.

Cheung, Yen, et al.. (2015). Uplifting citizens' participation: A Gov 2.0 conceptual framework. 9–17. 5 indexed citations

16.

Cheung, Yen, et al.. (2014). Clusters and innovation: A case of the Colchagua wine cluster. Pacific Asia Conference on Information Systems. 9. 1 indexed citations

17.

Cheung, Yen, et al.. (2014). TOWARDS SUSTAINABILITY OF EMARKETPLACES. Journal of the Association for Information Systems. 294. 4 indexed citations

18.

Taniar, David, et al.. (2010). Mining Hierarchical Negative Association Rules.. Computer Systems: Science & Engineering. 25. 1 indexed citations

19.

Dang, Xuan Hong, Wee Keong Ng, Kok‐Leong Ong, & Vincent C. S. Lee. (2007). Discovering frequent sets from data streams with CPU constraint. Deakin Research Online (Deakin University). 121–128. 2 indexed citations

20.

Lee, Vincent C. S. & Xingjian Yang. (2006). An artificial immune system based learning algorithm for abnormal or fraudulence detection in data stream. 821–824. 2 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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