Sungjun Kwon

1.1k total citations · 1 hit paper
17 papers, 811 citations indexed

About

Sungjun Kwon is a scholar working on Biomedical Engineering, Cardiology and Cardiovascular Medicine and Computer Vision and Pattern Recognition. According to data from OpenAlex, Sungjun Kwon has authored 17 papers receiving a total of 811 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Biomedical Engineering, 8 papers in Cardiology and Cardiovascular Medicine and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Sungjun Kwon's work include ECG Monitoring and Analysis (8 papers), Non-Invasive Vital Sign Monitoring (7 papers) and Heart Rate Variability and Autonomic Control (4 papers). Sungjun Kwon is often cited by papers focused on ECG Monitoring and Analysis (8 papers), Non-Invasive Vital Sign Monitoring (7 papers) and Heart Rate Variability and Autonomic Control (4 papers). Sungjun Kwon collaborates with scholars based in South Korea, Singapore and Canada. Sungjun Kwon's co-authors include Sangwon Chae, Dong-Hyun Lee, Hyun-Seok Kim, Kwangsuk Park, Jeehoon Kim, Dong‐Seok Lee, Sungwon Kang, Jeongsu Lee, Gih Sung Chung and Hanbyul Kim and has published in prestigious journals such as Scientific Reports, Sensors and International Journal of Environmental Research and Public Health.

In The Last Decade

Sungjun Kwon

17 papers receiving 777 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.

Predicting Infectious Disease Using Deep Learning and Big Data

2018 196 citations Sangwon Chae, Sungjun Kwon et al. International Journal of Environmental Research and Public Health profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Sungjun Kwon South Korea	12	349	263	105	99	89	17	811
Ebrahim Nemati United States	17	481 1.4×	241 0.9×	15 0.1×	56 0.6×	77 0.9×	62	1.1k
Sara Casaccia Italy	14	183 0.5×	113 0.4×	61 0.6×	35 0.4×	49 0.6×	71	684
Micaela Morettini Italy	18	248 0.7×	303 1.2×	3 0.0×	54 0.5×	84 0.9×	120	887
Mia Folke Sweden	9	374 1.1×	105 0.4×	14 0.1×	46 0.5×	105 1.2×	31	664
Guohun Zhu Australia	15	168 0.5×	190 0.7×	19 0.2×	36 0.4×	10 0.1×	40	950
Ahmed Salih United Kingdom	11	51 0.1×	93 0.4×	16 0.2×	100 1.0×	35 0.4×	41	567
Ashenafi Zebene Woldaregay Norway	10	106 0.3×	117 0.4×	6 0.1×	34 0.3×	125 1.4×	23	940
Silvia Seoni Italy	10	124 0.4×	84 0.3×	25 0.2×	179 1.8×	24 0.3×	33	865
Raphaël Couronné France	6	52 0.1×	59 0.2×	19 0.2×	51 0.5×	59 0.7×	8	652
Anup Kumar Gupta India	14	140 0.4×	121 0.5×	25 0.2×	21 0.2×	39 0.4×	40	637

Countries citing papers authored by Sungjun Kwon

Since Specialization

Citations

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

Fields of papers citing papers by Sungjun Kwon

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sungjun Kwon

This figure shows the co-authorship network connecting the top 25 collaborators of Sungjun Kwon. A scholar is included among the top collaborators of Sungjun Kwon 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 Sungjun Kwon. Sungjun Kwon 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:

17 of 17 papers shown

1.

Lee, Dong-Hyun, et al.. (2022). Integrated Prediction of Harmful Algal Bloom Using Cnn Deep Learning Technology. SSRN Electronic Journal. 1 indexed citations

2.

Lee, Dong-Hyun, et al.. (2022). Integrated explainable deep learning prediction of harmful algal blooms. Technological Forecasting and Social Change. 185. 122046–122046. 35 indexed citations

3.

Chae, Sangwon, et al.. (2021). PM10 and PM2.5 real-time prediction models using an interpolated convolutional neural network. Scientific Reports. 11(1). 11952–11952. 87 indexed citations

4.

Chae, Sangwon, Sungjun Kwon, & Dong-Hyun Lee. (2018). Predicting Infectious Disease Using Deep Learning and Big Data. International Journal of Environmental Research and Public Health. 15(8). 1596–1596. 196 indexed citations breakdown →

5.

Kwon, Sungjun, Dong‐Seok Lee, Jeehoon Kim, et al.. (2016). Sinabro: A Smartphone-Integrated Opportunistic Electrocardiogram Monitoring System. Sensors. 16(3). 361–361. 10 indexed citations

6.

Kwon, Sungjun, Jeehoon Kim, Dong‐Seok Lee, & Kwangsuk Park. (2015). ROI analysis for remote photoplethysmography on facial video. PubMed. 2015. 4938–4941. 74 indexed citations

7.

Kim, Hanbyul, Hong Ji Lee, Sungjun Kwon, et al.. (2015). Unconstrained detection of freezing of Gait in Parkinson's disease patients using smartphone. PubMed. 2015. 3751–3754. 55 indexed citations

8.

Lee, Dong‐Seok, Jeehoon Kim, Sungjun Kwon, & Kwangsuk Park. (2015). Heart rate estimation from facial photoplethysmography during dynamic illuminance changes. PubMed. 2015. 2758–2761. 20 indexed citations

9.

Kwon, Sungjun, et al.. (2014). CardioGuard: A Brassiere-Based Reliable ECG Monitoring Sensor System for Supporting Daily Smartphone Healthcare Applications. Telemedicine Journal and e-Health. 20(12). 1093–1102. 9 indexed citations

10.

Kang, Seungwoo, Sungjun Kwon, Chungkuk Yoo, et al.. (2014). Sinabro. Institutional Knowledge (InK) - Institutional Knowledge at Singapore Management University (Singapore Management University). 1–6. 12 indexed citations

11.

Kim, Jeehoon, et al.. (2014). Highly wearable galvanic skin response sensor using flexible and conductive polymer foam. PubMed. 2014. 6631–6634. 32 indexed citations

12.

Kwon, Sungjun, Seungwoo Kang, Youngki Lee, Chungkuk Yoo, & Kwangsuk Park. (2014). Unobtrusive monitoring of ECG-derived features during daily smartphone use. PubMed. 2014. 4964–4967. 6 indexed citations

13.

Yoon, Heenam, Hanbyul Kim, Sungjun Kwon, & Kwangsuk Park. (2013). An Automated Motion Artifact Removal Algorithm in Electrocardiogram Based on Independent Component Analysis. 15–20. 3 indexed citations

14.

Kwon, Sungjun, et al.. (2012). Validation of heart rate extraction using video imaging on a built-in camera system of a smartphone. PubMed. 2012. 2174–2177. 189 indexed citations

15.

Kwon, Sungjun, et al.. (2011). Validation of heart rate extraction through an iPhone accelerometer. PubMed. 2011. 5260–5263. 38 indexed citations

16.

Kwon, Sungjun, et al.. (2009). Swan boat. 997–998. 15 indexed citations

17.

Kwon, Sungjun, et al.. (2009). Running or gaming. 345–348. 29 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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