Chong-Moo Lee

461 total citations
42 papers, 371 citations indexed

About

Chong-Moo Lee is a scholar working on Ocean Engineering, Artificial Intelligence and Aerospace Engineering. According to data from OpenAlex, Chong-Moo Lee has authored 42 papers receiving a total of 371 indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Ocean Engineering, 12 papers in Artificial Intelligence and 10 papers in Aerospace Engineering. Recurrent topics in Chong-Moo Lee's work include Underwater Vehicles and Communication Systems (31 papers), Target Tracking and Data Fusion in Sensor Networks (12 papers) and Maritime Navigation and Safety (11 papers). Chong-Moo Lee is often cited by papers focused on Underwater Vehicles and Communication Systems (31 papers), Target Tracking and Data Fusion in Sensor Networks (12 papers) and Maritime Navigation and Safety (11 papers). Chong-Moo Lee collaborates with scholars based in South Korea, United States and Japan. Chong-Moo Lee's co-authors include Pan-Mook Lee, Seok Won Hong, Byeong Hwa Jeon, Kihun Kim, Sea-Moon Kim, Hyun‐Taek Choi, Bong-Huan Jun, Yong-Kon Lim, Jun-Ho Oh and Jin-Yeong Park and has published in prestigious journals such as SHILAP Revista de lepidopterología, Ocean Engineering and IEEE Journal of Oceanic Engineering.

In The Last Decade

Chong-Moo Lee

38 papers receiving 321 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Chong-Moo Lee South Korea	10	277	128	115	63	61	42	371
A. Caffaz Italy	9	325 1.2×	117 0.9×	81 0.7×	48 0.8×	55 0.9×	21	416
Kihun Kim South Korea	8	265 1.0×	86 0.7×	126 1.1×	104 1.7×	49 0.8×	34	338
Szymon Krupiński France	10	226 0.8×	59 0.5×	165 1.4×	52 0.8×	103 1.7×	21	325
D.A. Smallwood United States	10	333 1.2×	285 2.2×	88 0.8×	59 0.9×	37 0.6×	10	418
Yunsai Chen China	10	177 0.6×	207 1.6×	60 0.5×	63 1.0×	24 0.4×	29	370
Hexiong Zhou China	11	318 1.1×	166 1.3×	117 1.0×	27 0.4×	114 1.9×	28	416
Sankar Nath Shome India	13	136 0.5×	197 1.5×	103 0.9×	25 0.4×	216 3.5×	42	451
Artur Wolek United States	12	104 0.4×	63 0.5×	165 1.4×	65 1.0×	68 1.1×	39	314
Shuangshuang Fan China	9	149 0.5×	39 0.3×	70 0.6×	40 0.6×	83 1.4×	34	309
Matteo Franchi Italy	10	219 0.8×	22 0.2×	145 1.3×	55 0.9×	73 1.2×	26	313

Countries citing papers authored by Chong-Moo Lee

Since Specialization

Citations

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

Fields of papers citing papers by Chong-Moo Lee

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chong-Moo 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 Chong-Moo Lee. The network helps show where Chong-Moo Lee may publish in the future.

Co-authorship network of co-authors of Chong-Moo Lee

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

All Works

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20 of 20 papers shown

Yeu, Tae–Kyeong, Hyungwoo Kim, Jin-Yeong Park, et al.. (2024). Conceptual Design of Autonomous Underwater Walking Robot for Mine Hunting. 1–4.

Ko, Nak Yong, et al.. (2016). Navigation of unmanned surface vehicle and detection of GPS abnormality by fusing multiple sensor measurements. 10. 1–5. 3 indexed citations

Byun, Sung‒Hoon, et al.. (2016). Cyclostationary analysis of underwater noise for vehicle propeller monitoring. 86. 1–4. 6 indexed citations

Ko, Nak Yong, et al.. (2016). Fusion of multiple sensor measurements for navigation of an unmanned marine surface vehicle. 332–334. 2 indexed citations

Byun, Sung‒Hoon, et al.. (2015). Prototype development of an underwater sound measurement module using four hydrophones. 1–4. 1 indexed citations

Lee, Chong-Moo, et al.. (2011). The Estimation of the Propulsion Performance of a UUV Using Commercial Thruster. Journal of Ocean Engineering and Technology. 25(1). 27–31. 3 indexed citations

Choi, Hyun‐Taek, et al.. (2010). Implementation of Deep-sea UUV Precise Underwater Navigation based on Multiple Sensor Fusion. Journal of Ocean Engineering and Technology. 24(3). 46–51. 1 indexed citations

Lee, Chong-Moo, et al.. (2009). An Estimation Technique for the Thrust Performance of AUVs. Journal of Ocean Engineering and Technology. 23(4). 47–51. 1 indexed citations

Choi, Hyun‐Taek, Kihun Kim, Pan-Mook Lee, Chong-Moo Lee, & Bong-Huan Jun. (2009). Introduction to ROV and Motion Control & Signal Processing for ROV (Remotely Operated Vehicle) Hemire. Journal of the Korean Society for Precision Engineering. 26(5). 41–47. 5 indexed citations

10.

Joung, Tae-Hwan, et al.. (2008). A study on the pressure vessel design, structural analysis and pressure test of a 6000 m depth-rated unmanned underwater vehicle. Ships and Offshore Structures. 3(3). 205–214. 12 indexed citations

11.

Joung, Tae-Hwan, et al.. (2007). Study on the Design, Manufacture, and Pressure Test of a Pressure Vessel Model. Journal of Ocean Engineering and Technology. 21(6). 101–106. 2 indexed citations

12.

Lee, Pan-Mook, Bong-Huan Jun, Jihong Li, et al.. (2006). Navigation and Control System of a Deep-sea Unmanned Underwater Vehicle 'HEMIRE'. 1–8. 10 indexed citations

13.

Joung, Tae-Hwan, Chong-Moo Lee, Pan-Mook Lee, et al.. (2005). A Study On the Pressure Vessel Design, Structural Analysis And Pressure Test of a 6,000 M Depth-rated Unmanned Underwater Vehicle. 1 indexed citations

14.

Lee, Chong-Moo, Pan-Mook Lee, Seok Won Hong, Sea-Moon Kim, & Woojae Seong. (2005). Underwater Navigation System Based On Inertial Sensor And Doppler Velocity Log Using Indirect Feedback Kalman Filter. International Journal of Offshore and Polar Engineering. 15(2). 34 indexed citations

15.

Lee, Pan-Mook, et al.. (2005). Design Optimization of Pressure Vessel of Small Autonomous Underwater Vehicle. Journal of Ocean Engineering and Technology. 19(1). 95–99. 3 indexed citations

16.

Lee, Chong-Moo, et al.. (2004). A Study on the Results of the Pressure Vessel Design, Structural Analysis, and Pressure Test of the Semi-Autonomous Underwater Vehicle (SAUV). Journal of Ocean Engineering and Technology. 18(4). 52–58. 7 indexed citations

17.

Lee, Pan-Mook, et al.. (2004). A Hybrid Navigation System for Underwater Unmanned Vehicles, Using a Range Sonar. Journal of Ocean Engineering and Technology. 18(4). 33–39. 9 indexed citations

18.

Lee, Pan-Mook, Chong-Moo Lee, Byeong Hwa Jeon, et al.. (2002). System design and quasi-sliding mode control of an AUV for ocean research and monitoring. 179–184. 2 indexed citations

19.

Hong, Seok Won, Pan-Mook Lee, Byeong Hwa Jeon, & Chong-Moo Lee. (2000). Design of an underwater vehicle-mounted manipulator system and non-regressor based adaptive control. The Proceedings of the ... International Offshore and Polar Engineering Conference. 2. 314–319. 3 indexed citations

20.

Lee, Pan-Mook, et al.. (1997). A Hybrid Navigation System For Underwater Robotic Vehicles. The Proceedings of the ... International Offshore and Polar Engineering Conference. 2. 93–99. 1 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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