Mario Tanda

1.2k citations
87 papers · 871 · h-index 17

Impact in

Papers in

Mario Tanda

78 papers receiving 738 citations

Peers

Mario Tanda
Comparison fields: 5 of 32
  • Computer Networks and Communications 533
  • Electrical and Electronic Engineering 758
  • Signal Processing 140
  • Aerospace Engineering 63
  • Artificial Intelligence 69
Replace Zorica Nikolić with:
Zorica Nikolić Serbia
Kareem E. Baddour Canada
Norbert Goertz Austria
Rausley A. A. de Souza Brazil
Gonzalo Vazquez-Vilar Spain
Jwo-Yuh Wu Taiwan
Jungsun Um South Korea
Srikrishna Bhashyam India
Zoran Zvonar United States
Dominik Seethaler Austria
Mario Tanda relative to Zorica Nikolić Serbia Zorica Nikolić's profile →
Citations per field
00.5×4.8×
Zorica Nikolić · 1×
Citations per year

Countries citing papers authored by Mario Tanda

Since Specialization
Citations

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

Fields of papers citing papers by Mario Tanda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 10 scholars most cited alongside Mario Tanda, 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 Mario Tanda Line = papers co-authored together Mario Tanda links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 87 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200976
2 200449
3 200748
4 200245
5 200841
6 200935
7 201228
8 199228
9 201525
10 200122
11 200221
12 200920
13 200619
14 201518
15 201518
16 201218
17 201518
18 201416
19 200415
20 200615

About Mario Tanda

Mario Tanda is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications, Signal Processing, Artificial Intelligence and Statistical and Nonlinear Physics, having authored 87 papers that have together received 871 indexed citations. Recurring topics across this work include Advanced Wireless Communication Techniques (56 papers), Wireless Communication Networks Research (54 papers), PAPR reduction in OFDM (46 papers), Blind Source Separation Techniques (21 papers), Power Line Communications and Noise (16 papers), Distributed Sensor Networks and Detection Algorithms (13 papers), Optical Network Technologies (12 papers) and Advanced Power Amplifier Design (6 papers). The work is most often cited by research in Computer Networks and Communications (533 citations), Electrical and Electronic Engineering (758 citations), Signal Processing (140 citations), Aerospace Engineering (63 citations) and Artificial Intelligence (69 citations). Mario Tanda has collaborated with scholars based in Italy, France and United States. Frequent co-authors include Tilde Fusco, Davide Mattera, Maurice Bellanger, Luciano Izzo, Antonio Napolitano, H. Vincent Poor, L. Paura, G. Fedele, Luigi Paura and Valentina De Angelis. Their work appears in journals such as Signal Processing, IEEE Transactions on Communications, European Transactions on Telecommunications, The Journal of the Acoustical Society of America and IEEE Transactions on Signal Processing.

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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