Steven K. Huang

3.6k citations
74 papers · 2.6k indexed · h-index 29

Steven K. Huang

70 papers receiving 2.6k citations

Peers

Steven K. Huang
Comparison fields: 5 of 119
  • Pulmonary and Respiratory Medicine 1.4k
  • Hepatology 142
  • Genetics 137
  • Immunology 259
  • Cancer Research 179
Replace Jason Jungsik Song with:
Jason Jungsik Song South Korea
Harikrishna Tanjore United States
Carina Becerril Mexico
Min‐Chan Park South Korea
Brigham C. Willis United States
Christina E. Barkauskas United States
Mark Toshner United Kingdom
Norihiko Sakai Japan
Nasreen Khalil Canada
Jannie Marie Bülow Sand Denmark
Steven K. Huang relative to Jason Jungsik Song South Korea Jason Jungsik Song's profile →
Citations per field
00.5×4.5×
Jason Jungsik Song · 1×
Citations per year

Countries citing papers authored by Steven K. Huang

Since Specialization
Citations

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

Fields of papers citing papers by Steven K. Huang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Steven K. Huang. 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 Steven K. Huang. The network helps show where Steven K. Huang may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Steven K. Huang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Steven K. Huang Line = papers co-authored together Steven K. Huang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20248
3 20242
4 202317
5 202250
6 202115
7 202039
8 202031
9 201926
10 201824
11 201822
12 201630
13 201625
14 201559
15 201525
16 201418
17 201355
18 2010114
19 200826
20 200760

About Steven K. Huang

Steven K. Huang is a scholar working on Pulmonary and Respiratory Medicine, Issues, ethics and legal aspects and Health Informatics, having authored 74 papers that have together received 2.6k indexed citations. Recurring topics across this work include Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (37 papers), Neonatal Respiratory Health Research (14 papers), Peptidase Inhibition and Analysis (8 papers), Occupational and environmental lung diseases (7 papers), Medical Imaging and Pathology Studies (7 papers), Pulmonary Hypertension Research and Treatments (7 papers), Epigenetics and DNA Methylation (5 papers) and Occupational exposure and asthma (4 papers). The work is most often cited by research in Pulmonary and Respiratory Medicine (1.4k citations), Hepatology (142 citations) and Genetics (137 citations). Steven K. Huang has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Marc Peters‐Golden, Eric S. White, Anne M. Scruggs, Scott H. Wettlaufer, Cory M. Hogaboam, Jeffrey C. Horowitz, Kevin R. Flaherty, Jeffrey L. Myers, Fernando J. Martínez and David M. Aronoff. Their work appears in journals such as Nucleic Acids Research, Journal of Biological Chemistry and Journal of Clinical Investigation.

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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