Mario Goldenbaum

46 total papers · 976 total citations
33 papers, 659 citations indexed

About

Mario Goldenbaum is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering and Artificial Intelligence. According to data from OpenAlex, Mario Goldenbaum has authored 33 papers receiving a total of 659 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Computer Networks and Communications, 22 papers in Electrical and Electronic Engineering and 5 papers in Artificial Intelligence. Recurrent topics in Mario Goldenbaum's work include Wireless Communication Security Techniques (15 papers), Cooperative Communication and Network Coding (15 papers) and Energy Efficient Wireless Sensor Networks (13 papers). Mario Goldenbaum is often cited by papers focused on Wireless Communication Security Techniques (15 papers), Cooperative Communication and Network Coding (15 papers) and Energy Efficient Wireless Sensor Networks (13 papers). Mario Goldenbaum collaborates with scholars based in Germany, United States and Israel. Mario Goldenbaum's co-authors include Sławomir Stańczak, Holger Boche, H. Vincent Poor, Andreas Kortke, Shlomo Shamai, Alex Dytso, Meng Zheng, Haibin Yu, Wei Yang and Stefan Valentin and has published in prestigious journals such as IEEE Transactions on Signal Processing, IEEE Access and IEEE Transactions on Communications.

In The Last Decade

Mario Goldenbaum

33 papers receiving 644 citations

Author Peers

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

Author						Papers	Cites
Mario Goldenbaum	463	418	180	50	44	33	659
Wei-Cheng Liao	515 1.1×	398 1.0×	115 0.6×	73 1.5×	92 2.1×	26	738
Sindri Magnússon	312 0.7×	190 0.5×	124 0.7×	32 0.6×	93 2.1×	48	587
SaiDhiraj Amuru	329 0.7×	380 0.9×	151 0.8×	121 2.4×	15 0.3×	47	603
C.W. Baum	290 0.6×	365 0.9×	148 0.8×	39 0.8×	25 0.6×	47	562
Lei Wang	280 0.6×	329 0.8×	101 0.6×	34 0.7×	22 0.5×	61	573
Zhengdao Wang	505 1.1×	382 0.9×	50 0.3×	65 1.3×	38 0.9×	22	584
Krzysztof Wesołowski	562 1.2×	287 0.7×	58 0.3×	42 0.8×	34 0.8×	56	661
Tanumay Datta	671 1.4×	414 1.0×	64 0.4×	103 2.1×	32 0.7×	17	739
Sameer Pawar	443 1.0×	523 1.3×	189 1.1×	23 0.5×	80 1.8×	32	735
Maziar Sanjabi	345 0.7×	274 0.7×	290 1.6×	78 1.6×	94 2.1×	28	741

Countries citing papers authored by Mario Goldenbaum

Since Specialization

Citations

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

Fields of papers citing papers by Mario Goldenbaum

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mario Goldenbaum

This figure shows the co-authorship network connecting the top 25 collaborators of Mario Goldenbaum. A scholar is included among the top collaborators of Mario Goldenbaum 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 Mario Goldenbaum. Mario Goldenbaum 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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