Akhil Mathur

66 papers receiving 1.5k citations

Peers

Akhil Mathur
Comparison fields: 5 of 119
  • Human-Computer Interaction 249
  • Computer Vision and Pattern Recognition 545
  • Computer Science Applications 119
  • Signal Processing 152
  • Information Systems and Management 88
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Mi Zhang United States
Chulhong Min South Korea
Thomas Kirste Germany
Henk Muller United Kingdom
Denis Gračanin United States
Martin Halvey United Kingdom
Berardina De Carolis Italy
Luigi De Russis Italy
Jane Yung-jen Hsu Taiwan
Kurt Partridge United States
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Citations per year

Countries citing papers authored by Akhil Mathur

Since Specialization
Citations

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

Fields of papers citing papers by Akhil Mathur

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 68 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017162
2 2018109
3 2017108
4 2020100
5 200983
6 202279
7 200879
8 201852
9 201550
10 201848
11 201945
12 200938
13 201436
14 201634
15 202133
16 201630
17 201930
18 202227
19 201826
20 202124

About Akhil Mathur

Akhil Mathur is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Science Applications, Information Systems and Signal Processing, having authored 68 papers that have together received 1.5k indexed citations. Recurring topics across this work include Context-Aware Activity Recognition Systems (14 papers), Mobile Crowdsensing and Crowdsourcing (13 papers), ICT in Developing Communities (10 papers), Innovative Human-Technology Interaction (9 papers), Music and Audio Processing (8 papers), Child Development and Digital Technology (7 papers), Speech and Audio Processing (7 papers) and Personal Information Management and User Behavior (6 papers). The work is most often cited by research in Human-Computer Interaction (249 citations), Computer Vision and Pattern Recognition (545 citations), Computer Science Applications (119 citations), Signal Processing (152 citations) and Information Systems and Management (88 citations). Akhil Mathur has collaborated with scholars based in United Kingdom, United States and India. Frequent co-authors include Fahim Kawsar, Chulhong Min, Nicholas D. Lane, Alessandro Montanari, Claudio Forlivesi, John Canny, Sourav Bhattacharya, Matthew Kam, Anuj Kumar and Afra Mashhadi. Their work appears in journals such as Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies, IEEE Pervasive Computing, ACM Transactions on Embedded Computing Systems, ACM Transactions on Software Engineering and Methodology and IEEE Transactions on Mobile Computing.

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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