In Suck Suh

42 total papers · 539 total citations
32 papers, 362 citations indexed

About

In Suck Suh is a scholar working on Surgery, Dermatology and Epidemiology. According to data from OpenAlex, In Suck Suh has authored 32 papers receiving a total of 362 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Surgery, 17 papers in Dermatology and 7 papers in Epidemiology. Recurrent topics in In Suck Suh's work include Facial Rejuvenation and Surgery Techniques (8 papers), Reconstructive Facial Surgery Techniques (8 papers) and Dermatologic Treatments and Research (8 papers). In Suck Suh is often cited by papers focused on Facial Rejuvenation and Surgery Techniques (8 papers), Reconstructive Facial Surgery Techniques (8 papers) and Dermatologic Treatments and Research (8 papers). In Suck Suh collaborates with scholars based in South Korea, United States and Spain. In Suck Suh's co-authors include Hii Sun Jeong, Seong Hwan Kim, Sung Eun Chang, Seung Seog Han, Jung‐Im Na, Sam Yong Lee, Woohyung Lim, Ik Jun Moon, Sook Young Park and Seong‐Hoon Park and has published in prestigious journals such as SHILAP Revista de lepidopterología, Plastic & Reconstructive Surgery and Medicine.

In The Last Decade

In Suck Suh

30 papers receiving 351 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
In Suck Suh 174 125 73 64 52 32 362
Dorothee Dill‐Müller 150 0.9× 50 0.4× 17 0.2× 136 2.1× 9 0.2× 24 341
Teklu Legesse 84 0.5× 74 0.6× 7 0.1× 48 0.8× 21 0.4× 26 324
Saskia Maria Schnabl 123 0.7× 165 1.3× 21 0.3× 82 1.3× 5 0.1× 36 355
Mehdi Karami 90 0.5× 78 0.6× 20 0.3× 12 0.2× 6 0.1× 30 364
Joseph N. Mehrabi 241 1.4× 51 0.4× 17 0.2× 27 0.4× 5 0.1× 33 317
SHATTUCK W. HARTWELL 23 0.1× 138 1.1× 19 0.3× 50 0.8× 17 0.3× 24 324
Ik Jun Moon 150 0.9× 25 0.2× 14 0.2× 130 2.0× 88 1.7× 37 401
Jack Penn 62 0.4× 199 1.6× 78 1.1× 16 0.3× 4 0.1× 21 377
Cherng-Kang Perng 49 0.3× 168 1.3× 52 0.7× 10 0.2× 3 0.1× 30 356
Philippe Pouletaut 15 0.1× 83 0.7× 13 0.2× 11 0.2× 26 0.5× 43 379

Countries citing papers authored by In Suck Suh

Since Specialization
Citations

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

Fields of papers citing papers by In Suck Suh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by In Suck Suh. 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 In Suck Suh. The network helps show where In Suck Suh may publish in the future.

Co-authorship network of co-authors of In Suck Suh

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

All Works

Loading papers...

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026