Mónica Ribero

409 total citations
9 papers, 193 citations indexed

About

Mónica Ribero is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering and Aerospace Engineering. According to data from OpenAlex, Mónica Ribero has authored 9 papers receiving a total of 193 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 3 papers in Electrical and Electronic Engineering and 2 papers in Aerospace Engineering. Recurrent topics in Mónica Ribero's work include Privacy-Preserving Technologies in Data (5 papers), Millimeter-Wave Propagation and Modeling (3 papers) and Stochastic Gradient Optimization Techniques (2 papers). Mónica Ribero is often cited by papers focused on Privacy-Preserving Technologies in Data (5 papers), Millimeter-Wave Propagation and Modeling (3 papers) and Stochastic Gradient Optimization Techniques (2 papers). Mónica Ribero collaborates with scholars based in United States and Brazil. Mónica Ribero's co-authors include Haris Vikalo, Robert W. Heath, Yuyang Wang, Aldebaro Klautau, Anthony C. K. Soong, Gustavo de Veciana, Sinead A. Williamson, Reinaldo A. Valenzuela, Dmitry Chizhik and Carlos A. Duque and has published in prestigious journals such as IEEE Access, Pattern Recognition and IEEE Journal of Selected Topics in Signal Processing.

In The Last Decade

Mónica Ribero

7 papers receiving 192 citations

Peers

Mónica Ribero

EEE

AI

AE

CNC

IS

Dong-Jun Han South Korea

Vishal Gupta India

Marin Bertier France

Brian Proulx United States

S H Manjula India

Rafael G. L. D’Oliveira United States

Suriza Ahmad Zabidi Malaysia

Talha Faizur Rahman Italy

Aymen Boudguiga France

Muhammad Mukarram Bin Tariq United States

Dong-Jun Han South Korea

Mónica Ribero

76 ×0.6

EEE

138 ×1.9

AI

26 ×0.6

AE

87 ×2.8

CNC

26 ×1.6

IS

Citations per year, relative to Mónica Ribero Mónica Ribero (= 1×) peers Dong-Jun Han

Countries citing papers authored by Mónica Ribero

Since Specialization

Citations

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

Fields of papers citing papers by Mónica Ribero

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mónica Ribero

This figure shows the co-authorship network connecting the top 25 collaborators of Mónica Ribero. A scholar is included among the top collaborators of Mónica Ribero 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 Mónica Ribero. Mónica Ribero is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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9 of 9 papers shown

1.

Ribero, Mónica, Haris Vikalo, & Gustavo de Veciana. (2024). Federated Learning at Scale: Addressing Client Intermittency and Resource Constraints. IEEE Journal of Selected Topics in Signal Processing. 19(1). 60–73.

2.

Kong, William, Andrés Muñoz Medina, Mónica Ribero, & Umar Syed. (2024). DP-Auditorium: A Large-Scale Library for Auditing Differential Privacy. 110–126.

3.

Ribero, Mónica & Haris Vikalo. (2023). Reducing communication in federated learning via efficient client sampling. Pattern Recognition. 148. 110122–110122. 14 indexed citations

4.

Ribero, Mónica, Haris Vikalo, & Gustavo de Veciana. (2022). Federated Learning Under Intermittent Client Availability and Time-Varying Communication Constraints. IEEE Journal of Selected Topics in Signal Processing. 17(1). 98–111. 32 indexed citations

5.

Ribero, Mónica, et al.. (2022). Federating recommendations using differentially private prototypes. Pattern Recognition. 129. 108746–108746. 25 indexed citations

6.

Ribero, Mónica, Robert W. Heath, Haris Vikalo, Dmitry Chizhik, & Reinaldo A. Valenzuela. (2019). Deep Learning Propagation Models over Irregular Terrain. 4519–4523. 16 indexed citations

7.

Wang, Yuyang, Aldebaro Klautau, Mónica Ribero, Anthony C. K. Soong, & Robert W. Heath. (2019). MmWave Vehicular Beam Selection With Situational Awareness Using Machine Learning. IEEE Access. 7. 87479–87493. 74 indexed citations

8.

Wang, Yuyang, et al.. (2018). MmWave Vehicular Beam Training with Situational Awareness by Machine Learning. 1–6. 29 indexed citations

9.

Ribero, Mónica & Carlos A. Duque. (2004). The word length influence on waveform coding techniques based on wavelet transform applied to disturbance compression. 1. 139–143. 3 indexed citations

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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