Amit Baxi

527 citations
12 papers · 306 · h-index 6

Impact in

Papers in

Amit Baxi

12 papers receiving 284 citations

Peers

Amit Baxi
Comparison fields: 5 of 65
  • Applied Psychology 26
  • Health Information Management 22
  • Computer Networks and Communications 100
  • Information Systems 93
  • General Health Professions 77
Replace Leonardo Horn Iwaya with:
Leonardo Horn Iwaya Sweden
Emad Aghayi United States
Zhu Qing China
Ricardo Martinho Portugal
Hamid Mukhtar Pakistan
Abdulellah A. Alaboudi Saudi Arabia
Theodore Kotsilieris Greece
Ioannis Kouris Greece
William Van Woensel Canada
Andrei Vasilăţeanu Romania
Amit Baxi relative to Leonardo Horn Iwaya Sweden Leonardo Horn Iwaya's profile →
Citations per field
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Leonardo Horn Iwaya · 1×
Citations per year

Countries citing papers authored by Amit Baxi

Since Specialization
Citations

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

Fields of papers citing papers by Amit Baxi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 14 scholars most cited alongside Amit Baxi, 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 Amit Baxi Line = papers co-authored together Amit Baxi links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1 2012163
2 200983
3 202121
4 202214
5 20228
6 20066
7 20114
8 20102
9 20222
10 20251
11 20201
12 20241

About Amit Baxi

Amit Baxi is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering, Biomedical Engineering, Control and Systems Engineering and Computer Vision and Pattern Recognition, having authored 12 papers that have together received 306 indexed citations. Recurring topics across this work include Age of Information Optimization (4 papers), IoT and Edge/Fog Computing (4 papers), Energy Efficient Wireless Sensor Networks (2 papers), Context-Aware Activity Recognition Systems (2 papers), Wireless Body Area Networks (2 papers), IoT Networks and Protocols (1 paper), Innovative Energy Harvesting Technologies (1 paper) and Robotics and Automated Systems (1 paper). The work is most often cited by research in Applied Psychology (26 citations), Health Information Management (22 citations), Computer Networks and Communications (100 citations), Information Systems (93 citations) and General Health Professions (77 citations). Amit Baxi has collaborated with scholars based in India, United States and Germany. Frequent co-authors include Sasikanth Avancha, David Kotz, Dave Cavalcanti, Mark Eisen, Michael Paulitsch, Fabian Oboril, V. Natarajan, Lama Nachman, Ravishankar K. Iyer and Rath Vannithamby. Their work appears in journals such as ACM Computing Surveys, IEEE Open Journal of Vehicular Technology, IEEE Internet of Things Magazine and Proceedings of the AAAI Conference on Artificial Intelligence.

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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