Pourang Irani

6.0k citations
167 papers · 3.5k indexed · h-index 34

Pourang Irani

161 papers receiving 3.4k citations

Peers

Pourang Irani
Comparison fields: 5 of 109
  • Human-Computer Interaction 2.4k
  • Computer Vision and Pattern Recognition 1.6k
  • Cognitive Neuroscience 1.3k
  • Information Systems and Management 150
  • Computer Graphics and Computer-Aided Design 64
Replace Per Ola Kristensson with:
Per Ola Kristensson United Kingdom
Andreas Butz Germany
Raimund Dachselt Germany
Harald Reiterer Germany
François Guimbretière United States
Anthony Tang Canada
Michael Rohs Germany
Hai‐Ning Liang China
Jan Borchers Germany
Michel Beaudouin-Lafon France
Pourang Irani relative to Per Ola Kristensson United Kingdom Per Ola Kristensson's profile →
Citations per field
00.5×1.7×
Per Ola Kristensson · 1×
Citations per year

Countries citing papers authored by Pourang Irani

Since Specialization
Citations

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

Fields of papers citing papers by Pourang Irani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20241
3 20242
4 20244
5 20241
6 20226
7 20214
8 20202
9 202018
10 201714
11 201693
12 201526
13
Proceedings of the 16th international conference on Human-computer interaction with mobile devices & services
201463
14 20111
15 201037
16 20081
17 200729
18 20042
19 20040
20 20044

About Pourang Irani

Pourang Irani is a scholar working on Human-Computer Interaction, Cognitive Neuroscience and Computer Vision and Pattern Recognition, having authored 167 papers that have together received 3.5k indexed citations. Recurring topics across this work include Interactive and Immersive Displays (93 papers), Tactile and Sensory Interactions (77 papers), Data Visualization and Analytics (31 papers), Usability and User Interface Design (28 papers), Augmented Reality Applications (23 papers), Innovative Human-Technology Interaction (22 papers), Gaze Tracking and Assistive Technology (19 papers) and Virtual Reality Applications and Impacts (18 papers). The work is most often cited by research in Human-Computer Interaction (2.4k citations), Computer Vision and Pattern Recognition (1.6k citations) and Cognitive Neuroscience (1.3k citations). Pourang Irani has collaborated with scholars based in Canada, United Kingdom and United States. Frequent co-authors include Juan David Hincapié-Ramos, Sriram Subramanian, Barrett Ens, Sean Gustafson, Khalad Hasan, Xiang Guo, Xing-Dong Yang, Carl Gutwin, Teng Han and Fereshteh Amini.

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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