Michael C. Jin

71 papers receiving 1.3k citations

Peers

Michael C. Jin
Comparison fields: 5 of 139
  • Human-Computer Interaction 272
  • Genetics 144
  • Developmental and Educational Psychology 116
  • Endocrinology, Diabetes and Metabolism 134
  • Pathology and Forensic Medicine 129
Replace Marialuisa Martelli with:
Marialuisa Martelli Italy
Sandra Costa Portugal
Sandrine de Ribaupierre Canada
Michael B. Armstrong United States
Laura Hokkanen Finland
Jörg Trojan Germany
Jay J. Han United States
Sarah Squire United Kingdom
Rebecca Pauly United States
Heshan Liu United States
Michael C. Jin relative to Marialuisa Martelli Italy Marialuisa Martelli's profile →
Citations per field
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Marialuisa Martelli · 1×
Citations per year

Countries citing papers authored by Michael C. Jin

Since Specialization
Citations

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

Fields of papers citing papers by Michael C. Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael C. Jin. 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 Michael C. Jin. The network helps show where Michael C. Jin may publish in the future.

Co-authors

The 25 scholars most cited alongside Michael C. Jin, 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 Michael C. Jin Line = papers co-authored together Michael C. Jin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 78 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008439
2 2019124
3 2019103
4 201677
5 201650
6 202046
7 201941
8 202027
9 202324
10 201922
11 202021
12 202216
13 202016
14 202016
15 202016
16 201915
17 202214
18 201914
19 202013
20 201912

About Michael C. Jin

Michael C. Jin is a scholar working on Genetics, Cancer Research, Pulmonary and Respiratory Medicine, Pathology and Forensic Medicine and Public Health, Environmental and Occupational Health, having authored 78 papers that have together received 1.4k indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (9 papers), Glioma Diagnosis and Treatment (8 papers), Lymphoma Diagnosis and Treatment (7 papers), Opioid Use Disorder Treatment (3 papers), Brain Metastases and Treatment (3 papers), Sarcoma Diagnosis and Treatment (3 papers), Obstructive Sleep Apnea Research (3 papers) and Meningioma and schwannoma management (3 papers). The work is most often cited by research in Human-Computer Interaction (272 citations), Genetics (144 citations), Developmental and Educational Psychology (116 citations), Endocrinology, Diabetes and Metabolism (134 citations) and Pathology and Forensic Medicine (129 citations). Michael C. Jin has collaborated with scholars based in United States, Germany and Switzerland. Frequent co-authors include Nick Yee, Jeremy N. Bailenson, Andrew C. Beall, Jim Blascovich, Uchechukwu C. Megwalu, Z. Jason Qian, Tej D. Azad, Anand Veeravagu, Kara D. Meister and Zachary A. Medress. Their work appears in journals such as Blood, Neurosurgical FOCUS, Journal of Neurosurgery Pediatrics, World Neurosurgery and The Spine Journal.

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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