Uma Jayaram

1.1k citations
49 papers · 859 · h-index 14

Impact in

Papers in

Uma Jayaram

48 papers receiving 792 citations

Peers

Uma Jayaram
Comparison fields: 5 of 73
  • Industrial and Manufacturing Engineering 562
  • Human-Computer Interaction 139
  • Computer Vision and Pattern Recognition 235
  • Automotive Engineering 131
  • Management of Technology and Innovation 62
Replace Sankar Jayaram with:
Sankar Jayaram United States
Roland Menassa United States
Niki Kousi Greece
Michela Dalle Mura Italy
T. Szécsi Ireland
Terje K. Lien Norway
Marina Monti Italy
Rajit Gadh United States
Spyridon Koukas Greece
Christos Gkournelos Greece
Uma Jayaram relative to Sankar Jayaram United States Sankar Jayaram's profile →
Citations per field
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Sankar Jayaram · 1×
Citations per year

Countries citing papers authored by Uma Jayaram

Since Specialization
Citations

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

Fields of papers citing papers by Uma Jayaram

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 49 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1999231
2 200179
3 200674
4 200358
5 201044
6 200743
7 200342
8 200323
9 200423
10 200420
11 200118
12 200017
13 200916
14 200013
15 200013
16 200513
17 201111
18 20049
19 19999
20 20098

About Uma Jayaram

Uma Jayaram is a scholar working on Industrial and Manufacturing Engineering, Computational Mechanics, Control and Systems Engineering, Computer Vision and Pattern Recognition and Mechanical Engineering, having authored 49 papers that have together received 859 indexed citations. Recurring topics across this work include Manufacturing Process and Optimization (35 papers), 3D Shape Modeling and Analysis (8 papers), Semantic Web and Ontologies (7 papers), Ergonomics and Musculoskeletal Disorders (6 papers), Additive Manufacturing and 3D Printing Technologies (6 papers), Virtual Reality Applications and Impacts (5 papers), Simulation and Modeling Applications (5 papers) and Advanced Numerical Analysis Techniques (5 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (562 citations), Human-Computer Interaction (139 citations), Computer Vision and Pattern Recognition (235 citations), Automotive Engineering (131 citations) and Management of Technology and Innovation (62 citations). Uma Jayaram has collaborated with scholars based in United States, Japan and Egypt. Frequent co-authors include Sankar Jayaram, Kevin W. Lyons, Peter E. Hart, Yong Wang, Craig Palmer, Okjoon Kim, Judy M. Vance, Rajit Gadh, Hari Srinivasan and Youngjun Kim. Their work appears in journals such as Journal of Computing and Information Science in Engineering, Virtual Reality, IEEE Computer Graphics and Applications, Computers in Industry and Journal of Biomechanics.

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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