Cheolsoo Park

2.7k total citations
121 papers, 1.9k citations indexed

About

Cheolsoo Park is a scholar working on Cognitive Neuroscience, Biomedical Engineering and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Cheolsoo Park has authored 121 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Cognitive Neuroscience, 27 papers in Biomedical Engineering and 23 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Cheolsoo Park's work include EEG and Brain-Computer Interfaces (33 papers), Building Energy and Comfort Optimization (18 papers) and Non-Invasive Vital Sign Monitoring (15 papers). Cheolsoo Park is often cited by papers focused on EEG and Brain-Computer Interfaces (33 papers), Building Energy and Comfort Optimization (18 papers) and Non-Invasive Vital Sign Monitoring (15 papers). Cheolsoo Park collaborates with scholars based in South Korea, United States and United Kingdom. Cheolsoo Park's co-authors include Danilo P. Mandic, David Looney, Naveed ur Rehman, Michael Ungstrup, Preben Kidmose, Deuk-Woo Kim, Young‐Jin Kim, Godfried Augenbroe, Norden E. Huang and Alireza Ahrabian and has published in prestigious journals such as Scientific Reports, IEEE Access and IEEE Transactions on Biomedical Engineering.

In The Last Decade

Cheolsoo Park

102 papers receiving 1.9k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Cheolsoo Park South Korea	21	783	389	319	306	280	121	1.9k
Sarath Kodagoda Australia	25	990 1.3×	958 2.5×	61 0.2×	143 0.5×	102 0.4×	166	3.4k
A. Lay-Ekuakille Italy	31	374 0.5×	785 2.0×	99 0.3×	229 0.7×	239 0.9×	261	3.6k
Diego S. Benítez Ecuador	17	325 0.4×	427 1.1×	366 1.1×	489 1.6×	122 0.4×	151	1.9k
Radek Martínek Czechia	31	624 0.8×	1.0k 2.7×	114 0.4×	1.0k 3.4×	540 1.9×	322	4.1k
Chi Zhang China	24	611 0.8×	257 0.7×	48 0.2×	101 0.3×	124 0.4×	105	2.1k
Gui‐Bin Bian China	26	589 0.8×	765 2.0×	31 0.1×	193 0.6×	177 0.6×	140	2.9k
Fernando Morgado‐Dias Portugal	24	378 0.5×	464 1.2×	82 0.3×	123 0.4×	117 0.4×	143	2.3k
Gang Wang China	28	1.2k 1.5×	515 1.3×	25 0.1×	214 0.7×	298 1.1×	191	2.7k
Sawal Hamid Md Ali Malaysia	25	678 0.9×	649 1.7×	21 0.1×	250 0.8×	184 0.7×	218	3.0k
Anita Graser Germany	15	623 0.8×	95 0.2×	107 0.3×	57 0.2×	249 0.9×	72	1.4k

Countries citing papers authored by Cheolsoo Park

Since Specialization

Citations

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

Fields of papers citing papers by Cheolsoo Park

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Cheolsoo Park

This figure shows the co-authorship network connecting the top 25 collaborators of Cheolsoo Park. A scholar is included among the top collaborators of Cheolsoo Park 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 Cheolsoo Park. Cheolsoo Park 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

Park, Jongkil, et al.. (2025). Regression Model Employing Spiking Neural Network for Bio-Signal Analysis With Hardware Integration. IEEE Access. 13. 41456–41470.

Lee, Jiwoon, et al.. (2025). Designing Spiking Neural Network-Based Reinforcement Learning for 3D Robotic Arm Applications. Electronics. 14(3). 578–578. 1 indexed citations

Lee, Jihong, et al.. (2025). Designing a Remote Photoplethysmography-Based Heart Rate Estimation Algorithm During a Treadmill Exercise. Electronics. 14(5). 890–890.

Yoon, Sungmin, et al.. (2024). Brain-inspired learning rules for spiking neural network-based control: a tutorial. Biomedical Engineering Letters. 15(1). 37–55. 1 indexed citations

Charlton, Peter, et al.. (2024). Energy-Efficient PPG-Based Respiratory Rate Estimation Using Spiking Neural Networks. Sensors. 24(12). 3980–3980. 2 indexed citations

Kim, Jinseok, et al.. (2024). Predicting Car Rental Prices: A Comparative Analysis of Machine Learning Models. Electronics. 13(12). 2345–2345. 2 indexed citations

Kim, Sung Hyun & Cheolsoo Park. (2023). Correlation analysis between indoor/outdoor environment and occupants’ window adjustment behavior using explainable AI (XAI). Building Simulation Conference proceedings. 18. 1 indexed citations

Shin, Youngjoo, et al.. (2023). GAN-based patient information hiding for an ECG authentication system. Biomedical Engineering Letters. 13(2). 197–207. 4 indexed citations

Sohn, Illsoo, et al.. (2023). Intelligent Feature Selection for ECG-Based Personal Authentication Using Deep Reinforcement Learning. Sensors. 23(3). 1230–1230. 10 indexed citations

10.

Lee, Wongyu, et al.. (2023). Unsupervised Spiking Neural Network with Dynamic Learning of Inhibitory Neurons. Sensors. 23(16). 7232–7232. 6 indexed citations

11.

Park, Cheolsoo, et al.. (2023). Hierarchical Affinity Propagation for Reliable Integrated Multilayer V2X Networks. IEEE Internet of Things Journal. 10(18). 16316–16331. 5 indexed citations

12.

Kim, Nam‐Ho, et al.. (2022). Deep Learning Approach for Detecting Work-Related Stress Using Multimodal Signals. IEEE Sensors Journal. 22(12). 11892–11902. 36 indexed citations

13.

Cho, Young‐Ho, Cheolsoo Park, & Sang‐Won Yun. (2022). 4-Pole Tunable Absorptive Bandstop Filters Using Folded Coupled-Lines With an Inductor. IEEE Access. 10. 120191–120199. 3 indexed citations

14.

Park, Cheolsoo, et al.. (2022). Self-Optimizing Bluetooth Low Energy Networks for Industrial IoT Applications. IEEE Communications Letters. 27(1). 386–390. 11 indexed citations

15.

Cho, Young‐Ho, Cheolsoo Park, & Sang‐Won Yun. (2021). 0.7-1.0-GHz Switchable Dual-/Single-Band Tunable Bandpass Filter Using a Switchable J-Inverter. IEEE Access. 9. 16967–16974. 17 indexed citations

16.

Hariyani, Yuli Sun, et al.. (2020). End-To-End Deep Learning Architecture for Continuous Blood Pressure Estimation Using Attention Mechanism. Sensors. 20(8). 2338–2338. 98 indexed citations

17.

Kim, Youngjoo, et al.. (2018). Correlation Assisted Strong Uncorrelating Transform Complex Common Spatial Patterns for Spatially Distant Channel Data. Computational Intelligence and Neuroscience. 2018. 1–9. 1 indexed citations

18.

Kim, Youngjoo, et al.. (2016). Motor Imagery Classification Using Mu and Beta Rhythms of EEG with Strong Uncorrelating Transform Based Complex Common Spatial Patterns. Computational Intelligence and Neuroscience. 2016. 1–13. 82 indexed citations

19.

Song, JaeSeung, et al.. (2016). Estimation of Brain Connectivity during Motor Imagery Tasks using Noise-Assisted Multivariate Empirical Mode Decomposition. Journal of Electrical Engineering and Technology. 11(6). 1812–1824. 10 indexed citations

20.

Park, Cheolsoo. (2005). Transformation of Images on Apartment Depicted in Korean Popular Novels. Journal of the Architectural Institute of Korea. 21(1). 189–200. 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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