Jing Sha

1.3k citations
66 papers · 1.0k · h-index 16

Impact in

Papers in

Jing Sha

61 papers receiving 992 citations

Peers

Jing Sha
Comparison fields: 5 of 131
  • Endocrinology 185
  • Molecular Medicine 69
  • Signal Processing 76
  • Aging 10
  • Surfaces, Coatings and Films 35
Replace Junjie Zhang with:
Junjie Zhang United States
Shinya Kumagai Japan
Marnix Vlot Netherlands
Qian Xu United States
Anthony Kusalik Canada
Kehong Liu China
Jan A. Hiss Switzerland
Le Xiao China
Robert Chen United States
Jing Sha relative to Junjie Zhang United States Junjie Zhang's profile →
Citations per field
00.5×10×12.7×
Junjie Zhang · 1×
Citations per year

Countries citing papers authored by Jing Sha

Since Specialization
Citations

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

Fields of papers citing papers by Jing Sha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 66 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009167
2 201186
3 200679
4 200471
5 201060
6 201942
7 200540
8 200835
9 201229
10 202326
11 201223
12 201922
13 201521
14 200920
15 201820
16 201019
17 200415
18 201214
19 202214
20 201913

About Jing Sha

Jing Sha is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence, Biomedical Engineering, Information Systems and Computer Networks and Communications, having authored 66 papers that have together received 1.0k indexed citations. Recurring topics across this work include Advancements in Photolithography Techniques (13 papers), Nanofabrication and Lithography Techniques (6 papers), Semiconductor materials and devices (5 papers), Salmonella and Campylobacter epidemiology (4 papers), Advanced Malware Detection Techniques (4 papers), Integrated Circuits and Semiconductor Failure Analysis (4 papers), Intelligent Tutoring Systems and Adaptive Learning (4 papers) and Phase Equilibria and Thermodynamics (3 papers). The work is most often cited by research in Endocrinology (185 citations), Molecular Medicine (69 citations), Signal Processing (76 citations), Aging (10 citations) and Surfaces, Coatings and Films (35 citations). Jing Sha has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Ashok K. Chopra, A. A. Fadl, Christopher K. Ober, Tatiana E. Erova, Johanna C. Sierra, Amy J. Horneman, Giovanni Suárez, Gary R. Klimpel, Cristi L. Galindo and David W. Niesel. Their work appears in journals such as Infection and Immunity, Journal of Materials Chemistry, American Journal of Translational Research, Gene and INTERNATIONAL JOURNAL ON Advances in Information Sciences and Service Sciences.

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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