Edward Jay Wang

25 papers receiving 488 citations

Peers

Edward Jay Wang
Comparison fields: 5 of 82
  • Human-Computer Interaction 116
  • Cognitive Neuroscience 105
  • Cardiology and Cardiovascular Medicine 116
  • Biomedical Engineering 220
  • Computer Vision and Pattern Recognition 90
Replace Tomasz Kocejko with:
Tomasz Kocejko Poland
Adam Bujnowski Poland
Abhilash K. Pandya United States
Sašo Koceski North Macedonia
Kosuke Nakajima Japan
Suzanne Kieffer Belgium
Md Shafayet Hossain Bangladesh
Viswam Nathan United States
Raffaella Lanzarotti Italy
Tousif Ahmed United States
Edward Jay Wang relative to Tomasz Kocejko Poland Tomasz Kocejko's profile →
Citations per field
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Tomasz Kocejko · 1×
Citations per year

Countries citing papers authored by Edward Jay Wang

Since Specialization
Citations

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

Fields of papers citing papers by Edward Jay Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Edward Jay Wang. 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 Edward Jay Wang. The network helps show where Edward Jay Wang may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201783
2 201678
3 201874
4 201574
5 201742
6 201536
7 201716
8 202215
9 202313
10 202510
11 201810
12 20228
13 20198
14 20178
15 20175
16 20244
17 20234
18 20232
19 20242
20 20232

About Edward Jay Wang

Edward Jay Wang is a scholar working on Biomedical Engineering, General Health Professions, Cardiology and Cardiovascular Medicine, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging, having authored 28 papers that have together received 502 indexed citations. Recurring topics across this work include Non-Invasive Vital Sign Monitoring (10 papers), Mobile Health and mHealth Applications (6 papers), Context-Aware Activity Recognition Systems (5 papers), Optical Imaging and Spectroscopy Techniques (4 papers), Heart Rate Variability and Autonomic Control (4 papers), Breastfeeding Practices and Influences (4 papers), Gaze Tracking and Assistive Technology (3 papers) and Hemodynamic Monitoring and Therapy (3 papers). The work is most often cited by research in Human-Computer Interaction (116 citations), Cognitive Neuroscience (105 citations), Cardiology and Cardiovascular Medicine (116 citations), Biomedical Engineering (220 citations) and Computer Vision and Pattern Recognition (90 citations). Edward Jay Wang has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Shwetak Patel, Christian Holz, Alexandra Ion, Patrick Baudisch, William Li, Terry Gernsheimer, Elliot Saba, Lama Nachman, Mayank Goel and Mohit Jain. Their work appears in journals such as Scientific Reports, npj Digital Medicine, Science Advances, IEEE Pervasive Computing and Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies.

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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