Roberto La Rosa

65 total papers · 618 total citations
48 papers, 468 citations indexed

About

Roberto La Rosa is a scholar working on Electrical and Electronic Engineering, Mechanical Engineering and Computer Networks and Communications. According to data from OpenAlex, Roberto La Rosa has authored 48 papers receiving a total of 468 indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Electrical and Electronic Engineering, 24 papers in Mechanical Engineering and 14 papers in Computer Networks and Communications. Recurrent topics in Roberto La Rosa's work include Energy Harvesting in Wireless Networks (37 papers), Innovative Energy Harvesting Technologies (23 papers) and Wireless Power Transfer Systems (21 papers). Roberto La Rosa is often cited by papers focused on Energy Harvesting in Wireless Networks (37 papers), Innovative Energy Harvesting Technologies (23 papers) and Wireless Power Transfer Systems (21 papers). Roberto La Rosa collaborates with scholars based in Italy, Switzerland and France. Roberto La Rosa's co-authors include Patrizia Livreri, Carlo Trigona, Loreto Di Donato, Gino Sorbello, Catherine Dehollain, Salvatore Baglio, Filippo Pellitteri, Bruno Andò, G. Capponi and V. Boscaino and has published in prestigious journals such as Sensors, IEEE Transactions on Instrumentation and Measurement and IEEE Sensors Journal.

In The Last Decade

Roberto La Rosa

37 papers receiving 457 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Roberto La Rosa	396	152	107	67	66	48	468
Yoshiaki Narusue	361 0.9×	72 0.5×	93 0.9×	133 2.0×	59 0.9×	67	468
Danial Khan	429 1.1×	120 0.8×	26 0.2×	127 1.9×	14 0.2×	58	481
Jinwook Song	422 1.1×	54 0.4×	19 0.2×	75 1.1×	34 0.5×	50	478
Hang Zhang	405 1.0×	48 0.3×	109 1.0×	32 0.5×	17 0.3×	41	473
Jianxin Chu	337 0.9×	74 0.5×	34 0.3×	71 1.1×	54 0.8×	38	459
Qiwei Wang	301 0.8×	81 0.5×	82 0.8×	33 0.5×	23 0.3×	68	464
Christian Viehweger	328 0.8×	248 1.6×	83 0.8×	97 1.4×	6 0.1×	30	473
Shuichi Obayashi	458 1.2×	40 0.3×	48 0.4×	73 1.1×	39 0.6×	61	531
Chan Zhou	358 0.9×	29 0.2×	247 2.3×	40 0.6×	20 0.3×	58	506
Jasmin Grosinger	435 1.1×	69 0.5×	59 0.6×	119 1.8×	260 3.9×	72	542

Countries citing papers authored by Roberto La Rosa

Since Specialization

Citations

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

Fields of papers citing papers by Roberto La Rosa

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Roberto La Rosa. 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 Roberto La Rosa. The network helps show where Roberto La Rosa may publish in the future.

Co-authorship network of co-authors of Roberto La Rosa

This figure shows the co-authorship network connecting the top 25 collaborators of Roberto La Rosa. A scholar is included among the top collaborators of Roberto La Rosa based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Roberto La Rosa. Roberto La Rosa is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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