Se‐Jun Lee

3.6k total citations · 1 hit paper
50 papers, 3.0k citations indexed

About

Se‐Jun Lee is a scholar working on Biomedical Engineering, Cellular and Molecular Neuroscience and Automotive Engineering. According to data from OpenAlex, Se‐Jun Lee has authored 50 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Biomedical Engineering, 14 papers in Cellular and Molecular Neuroscience and 12 papers in Automotive Engineering. Recurrent topics in Se‐Jun Lee's work include 3D Printing in Biomedical Research (18 papers), Neuroscience and Neural Engineering (11 papers) and Advanced Combustion Engine Technologies (8 papers). Se‐Jun Lee is often cited by papers focused on 3D Printing in Biomedical Research (18 papers), Neuroscience and Neural Engineering (11 papers) and Advanced Combustion Engine Technologies (8 papers). Se‐Jun Lee collaborates with scholars based in United States, South Korea and Japan. Se‐Jun Lee's co-authors include Lijie Grace Zhang, Xuan Zhou, Haitao Cui, Shida Miao, Margaret Nowicki, Wei Zhu, Nathan J. Castro, Timothy Esworthy, Dong Nyoung Heo and Brent T. Harris and has published in prestigious journals such as SHILAP Revista de lepidopterología, Advanced Drug Delivery Reviews and Scientific Reports.

In The Last Decade

Se‐Jun Lee

46 papers receiving 2.9k citations

Hit Papers

4D physiologically adaptable cardiac patch: A 4-month in ... 2020 2026 2022 2024 2020 50 100 150

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Se‐Jun Lee United States 26 2.2k 1.0k 639 524 485 50 3.0k
Margaret Nowicki United States 18 2.5k 1.1× 1.3k 1.3× 553 0.9× 335 0.6× 552 1.1× 28 3.0k
Xuan Zhou United States 29 2.7k 1.2× 1.4k 1.3× 746 1.2× 280 0.5× 615 1.3× 50 3.5k
Nathan J. Castro United States 25 1.9k 0.9× 938 0.9× 652 1.0× 183 0.3× 459 0.9× 49 2.7k
Pranav Soman United States 26 2.3k 1.0× 1.1k 1.1× 535 0.8× 144 0.3× 443 0.9× 59 3.1k
Haitao Cui United States 35 3.7k 1.7× 1.9k 1.9× 1.0k 1.6× 354 0.7× 926 1.9× 58 4.8k
Alexandra L. Rutz United States 15 1.8k 0.8× 809 0.8× 311 0.5× 322 0.6× 146 0.3× 20 2.5k
Stephanie M. Willerth Canada 34 2.6k 1.2× 852 0.8× 1.2k 1.8× 1.2k 2.2× 302 0.6× 114 4.3k
Mark A. Skylar‐Scott United States 18 3.8k 1.7× 1.7k 1.7× 563 0.9× 302 0.6× 465 1.0× 28 5.0k
Joshua W. Tashman United States 18 2.0k 0.9× 1.0k 1.0× 391 0.6× 197 0.4× 102 0.2× 21 2.5k

Countries citing papers authored by Se‐Jun Lee

Since Specialization
Citations

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

Fields of papers citing papers by Se‐Jun Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Se‐Jun 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 Se‐Jun Lee. The network helps show where Se‐Jun Lee may publish in the future.

Co-authorship network of co-authors of Se‐Jun Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Se‐Jun Lee. A scholar is included among the top collaborators of Se‐Jun 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 Se‐Jun Lee. Se‐Jun Lee 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.
2.
Lee, Se‐Jun, et al.. (2023). Analysis of the Effectiveness of the Multiple Short Range High Speed Target According to the Engagement Distance. Journal of Korean Institute of Industrial Engineers. 49(5). 448–454.
3.
Hann, Sung Yun, Haitao Cui, Timothy Esworthy, et al.. (2021). Dual 3D printing for vascularized bone tissue regeneration. Acta Biomaterialia. 123. 263–274. 73 indexed citations
4.
Miao, Shida, Haitao Cui, Timothy Esworthy, et al.. (2020). 4D Self‐Morphing Culture Substrate for Modulating Cell Differentiation. Advanced Science. 7(6). 1902403–1902403. 65 indexed citations
5.
Asheghali, Darya, Se‐Jun Lee, Andreas Furchner, et al.. (2020). Enhanced neuronal differentiation of neural stem cells with mechanically enhanced touch-spun nanofibrous scaffolds. Nanomedicine Nanotechnology Biology and Medicine. 24. 102152–102152. 15 indexed citations
6.
Cui, Haitao, Chengyu Liu, Timothy Esworthy, et al.. (2020). 4D physiologically adaptable cardiac patch: A 4-month in vivo study for the treatment of myocardial infarction. Science Advances. 6(26). eabb5067–eabb5067. 169 indexed citations breakdown →
7.
Lee, Se‐Jun, Darya Asheghali, Raju Timsina, et al.. (2019). Touch-Spun Nanofibers for Nerve Regeneration. ACS Applied Materials & Interfaces. 12(2). 2067–2075. 28 indexed citations
8.
Hann, Sung Yun, Haitao Cui, Timothy Esworthy, et al.. (2019). Recent advances in 3D printing: vascular network for tissue and organ regeneration. Translational research. 211. 46–63. 100 indexed citations
9.
Heo, Dong Nyoung, Se‐Jun Lee, Raju Timsina, et al.. (2019). Development of 3D printable conductive hydrogel with crystallized PEDOT:PSS for neural tissue engineering. Materials Science and Engineering C. 99. 582–590. 223 indexed citations
10.
Zhou, Xuan, Haitao Cui, Margaret Nowicki, et al.. (2018). Three-Dimensional-Bioprinted Dopamine-Based Matrix for Promoting Neural Regeneration. ACS Applied Materials & Interfaces. 10(10). 8993–9001. 121 indexed citations
11.
Jeong, Jaehoon, Se‐Jun Lee, Tae Oh, et al.. (2017). STMAC: Spatio-Temporal Coordination-Based MAC Protocol for Driving Safety in Urban Vehicular Networks. IEEE Transactions on Intelligent Transportation Systems. 19(5). 1520–1536. 8 indexed citations
12.
Lee, Se‐Jun, et al.. (2017). Investigation of Combustion Regimes in Super Lean-burn SI Engines Using the Turbulent Combustion Diagram. Transactions of the Society of Automotive Engineers of Japan. 48(4). 1 indexed citations
13.
Heo, Dong Nyoung, et al.. (2017). Enhanced bone tissue regeneration using a 3D printed microstructure incorporated with a hybrid nano hydrogel. Nanoscale. 9(16). 5055–5062. 130 indexed citations
14.
Miao, Shida, Nathan J. Castro, Margaret Nowicki, et al.. (2017). 4D printing of polymeric materials for tissue and organ regeneration. Materials Today. 20(10). 577–591. 311 indexed citations
16.
Lee, Se‐Jun, et al.. (2016). Development of Novel 3-D Printed Scaffolds With Core-Shell Nanoparticles for Nerve Regeneration. IEEE Transactions on Biomedical Engineering. 64(2). 408–418. 70 indexed citations
17.
Zhu, Wei, Se‐Jun Lee, Nathan J. Castro, et al.. (2016). Synergistic Effect of Cold Atmospheric Plasma and Drug Loaded Core-shell Nanoparticles on Inhibiting Breast Cancer Cell Growth. Scientific Reports. 6(1). 21974–21974. 87 indexed citations
18.
Lee, Se‐Jun, Margaret Nowicki, Brent T. Harris, & Lijie Grace Zhang. (2016). Fabrication of a Highly Aligned Neural Scaffold via a Table Top Stereolithography 3D Printing and Electrospinning . Tissue Engineering Part A. 23(11-12). 491–502. 133 indexed citations
19.
Kim, Hyeon-Su, Minsu Kim, Se‐Jun Lee, et al.. (2006). Endoscopic Sphincterotomy Plus Endoscopic Papillary Large BalloonDilatation for Large Bile Duct Stones. Clinical Endoscopy. 32(3). 184–189. 3 indexed citations
20.
Lee, Dong‐Gi, et al.. (2005). Tubular Adenoma of the Common Bile Duct: Endoscopic Diagnosis and Treatment. Clinical Endoscopy. 31(3). 193–197.

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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