Aman Parnami

587 citations
27 papers · 396 · h-index 11

Impact in

Papers in

    • Interactive and Immersive Displays 15
    • Innovative Human-Technology Interaction 9
    • Gaze Tracking and Assistive Technology 3
    • Virtual Reality Applications and Impacts 2
    • Tactile and Sensory Interactions 8

Aman Parnami

26 papers receiving 385 citations

Peers

Aman Parnami
Comparison fields: 5 of 69
  • Human-Computer Interaction 160
  • Computer Vision and Pattern Recognition 101
  • Cognitive Neuroscience 83
  • Computer Science Applications 20
  • Public Health, Environmental and Occupational Health 76
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Citations per field
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Citations per year

Countries citing papers authored by Aman Parnami

Since Specialization
Citations

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

Fields of papers citing papers by Aman Parnami

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 21 scholars most cited alongside Aman Parnami, 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 Aman Parnami Line = papers co-authored together Aman Parnami links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Leveraging Context to Support Automated Food Recognition in Restaurants
201572
2 201350
3 202142
4 201339
5 201629
6 201928
7 202225
8 201919
9 202011
10 201311
11 201910
12 20219
13 20198
14 20167
15 20236
16 20236
17 20165
18 20235
19 20193
20 20213

About Aman Parnami

Aman Parnami is a scholar working on Human-Computer Interaction, Cognitive Neuroscience, Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology and Mechanical Engineering, having authored 27 papers that have together received 396 indexed citations. Recurring topics across this work include Interactive and Immersive Displays (15 papers), Innovative Human-Technology Interaction (9 papers), Tactile and Sensory Interactions (8 papers), Gaze Tracking and Assistive Technology (3 papers), Virtual Reality Applications and Impacts (2 papers), Human Motion and Animation (2 papers), Nutritional Studies and Diet (2 papers) and Music Technology and Sound Studies (2 papers). The work is most often cited by research in Human-Computer Interaction (160 citations), Computer Vision and Pattern Recognition (101 citations), Cognitive Neuroscience (83 citations), Computer Science Applications (20 citations) and Public Health, Environmental and Occupational Health (76 citations). Aman Parnami has collaborated with scholars based in India, United States and Australia. Frequent co-authors include Gregory D. Abowd, Edison Thomaz, Irfan Essa, Vinay Bettadapura, Jainendra Shukla, Jonathan Bidwell, Gabriel Reyes, Angus G. Forbes, Jason Wu and W. Keith Edwards. Their work appears in journals such as Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies, Proceedings of the ACM on Human-Computer Interaction, SMARTech Repository (Georgia Institute of Technology) and Designing Interactive Systems Conference.

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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