Miguel Rio

2.1k total citations
106 papers, 1.3k citations indexed

About

Miguel Rio is a scholar working on Computer Networks and Communications, Artificial Intelligence and Electrical and Electronic Engineering. According to data from OpenAlex, Miguel Rio has authored 106 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 71 papers in Computer Networks and Communications, 31 papers in Artificial Intelligence and 17 papers in Electrical and Electronic Engineering. Recurrent topics in Miguel Rio's work include Network Traffic and Congestion Control (30 papers), Caching and Content Delivery (24 papers) and Software-Defined Networks and 5G (21 papers). Miguel Rio is often cited by papers focused on Network Traffic and Congestion Control (30 papers), Caching and Content Delivery (24 papers) and Software-Defined Networks and 5G (21 papers). Miguel Rio collaborates with scholars based in United Kingdom, Spain and Portugal. Miguel Rio's co-authors include Miguel Rocha, Paulo Cortez, Pedro Sousa, David Griffin, Andrew W. Moore, Hamed Haddadi, Richard Mortier, Rául Landa, Richard G. Clegg and Truong Khoa Phan and has published in prestigious journals such as Brain, IEEE Communications Surveys & Tutorials and Expert Systems with Applications.

In The Last Decade

Miguel Rio

100 papers receiving 1.2k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Miguel Rio United Kingdom 18 663 268 211 178 134 106 1.3k
Theodore L. Willke United States 17 457 0.7× 320 1.2× 395 1.9× 257 1.4× 288 2.1× 57 1.3k
Ping Xiong China 21 195 0.3× 535 2.0× 165 0.8× 198 1.1× 108 0.8× 106 1.2k
Jinli Cao Australia 26 506 0.8× 827 3.1× 95 0.5× 514 2.9× 211 1.6× 116 1.8k
Heli Sun China 21 214 0.3× 733 2.7× 128 0.6× 236 1.3× 127 0.9× 88 1.6k
Giuseppe Di Fatta United Kingdom 16 526 0.8× 245 0.9× 96 0.5× 217 1.2× 229 1.7× 70 1.0k
Mohammed Al-Sarem Saudi Arabia 24 266 0.4× 639 2.4× 97 0.5× 365 2.1× 181 1.4× 75 1.5k
Muhammad Ilyas Pakistan 18 458 0.7× 257 1.0× 291 1.4× 260 1.5× 221 1.6× 106 1.3k
Zhen Huang China 24 158 0.2× 725 2.7× 180 0.9× 147 0.8× 390 2.9× 131 1.6k
Hazem Hajj Lebanon 23 211 0.3× 1.3k 4.7× 234 1.1× 386 2.2× 180 1.3× 121 1.9k

Countries citing papers authored by Miguel Rio

Since Specialization
Citations

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

Fields of papers citing papers by Miguel Rio

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Miguel Rio

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

All Works

20 of 20 papers shown
1.
Clayman, Stuart, Müge Sayıt, David Griffin, & Miguel Rio. (2024). Using Edge-Based Packet Trimming for Effective Bandwidth Utilization in 6G. 54–62. 1 indexed citations
2.
El‐kenawy, El‐Sayed M., et al.. (2023). Advanced Guided Whale Optimization Algorithm for Feature Selection in BlazePose Action Recognition. Intelligent Automation & Soft Computing. 37(3). 2767–2782. 3 indexed citations
3.
Rio, Miguel, et al.. (2023). BlazePose-Based Action Recognition with Feature Selection Using Stochastic Fractal Search Guided Whale Optimization. UCL Discovery (University College London). 1–5. 1 indexed citations
4.
Rio, Miguel, et al.. (2022). Skeleton Split Strategies for Spatial Temporal Graph Convolution Networks. Computers, materials & continua/Computers, materials & continua (Print). 71(3). 4643–4658. 5 indexed citations
5.
Nauck, Detlef, et al.. (2020). Benchmarking Video Service Quality: Quantifying the Viewer Impact of Loss-Related Impairments. IEEE Transactions on Network and Service Management. 17(3). 1640–1652. 4 indexed citations
6.
Howett, David, Richard N. Henson, Miguel Rio, et al.. (2019). Differentiation of mild cognitive impairment using an entorhinal cortex-based test of virtual reality navigation. Brain. 142(6). 1751–1766. 141 indexed citations
7.
Griffin, David, Nikolaos Zioulis, Truong Khoa Phan, et al.. (2018). Quality of Experience for 3-D Immersive Media Streaming. IEEE Transactions on Broadcasting. 64(2). 379–391. 24 indexed citations
8.
Camacho, Valle, Adolfo Gómez‐Grande, David García-Solís, et al.. (2018). PET amiloide en enfermedades neurodegenerativas que cursan con demencia. Revista Española de Medicina Nuclear e Imagen Molecular. 37(6). 397–406. 3 indexed citations
9.
Li, Jian, Truong Khoa Phan, Wei Koong Chai, et al.. (2018). DR-Cache: Distributed Resilient Caching with Latency Guarantees. 441–449. 36 indexed citations
10.
Clegg, Richard G., Rául Landa, & Miguel Rio. (2013). Criticisms of modelling packet traffic using long-range dependence (extended version). arXiv (Cornell University). 2 indexed citations
11.
Ramos-Font, C., Miguel Rio, Antonio Rodrı́guez-Fernández, R. Sánchez Sánchez, & J.M. Llamas Elvira. (2011). Tomografía por emisión de positrones con 18F-fluorodesoxiglucosa en la evaluación preoperatoria de lesiones de vesícula biliar sospechosas de malignidad. Utilidad diagnóstica e impacto clínico. Revista Española de Medicina Nuclear. 30(5). 267–275. 8 indexed citations
12.
Sánchez, R. Sánchez, et al.. (2011). Utilidad de la PET/TAC en la estadificación mediastínica del cáncer de pulmón de células no pequeñas en estadio III (N2). Revista Española de Medicina Nuclear. 30(4). 211–216. 5 indexed citations
13.
Ramos-Font, C., Miguel Rio, Antonio Rodrı́guez-Fernández, R. Sánchez Sánchez, & J.M. Llamas Elvira. (2011). Positron tomography with 18F-fluorodeoxyglucose in the preoperative evaluation of gallbladder lesions suspicious of malignancy: Diagnostic utility and clinical impact. Revista Española de Medicina Nuclear. 30(5). 267–275. 11 indexed citations
14.
Thomsen, Benn C., Cyril C. Renaud, Seb J. Savory, et al.. (2010). Introducing scenario based learning: Experiences from an undergraduate electronic and electrical engineering course. 953–958. 10 indexed citations
15.
Ramos-Font, C., et al.. (2009). Estadificación del cáncer de vesícula mediante tomografía de positrones con 18F-fluorodesoxiglucosa. Revista Española de Medicina Nuclear. 28(2). 74–77. 7 indexed citations
16.
Rio, Miguel, et al.. (2009). Two algorithms for network size estimation for master/slave ad hoc networks. 1–3. 11 indexed citations
17.
Fernández, Antonio Rodríguez, et al.. (2007). Estadificación del cáncer de pulmón de células no pequeñas. Utilidad de la imagen estructural (TAC) y funcional (FDG-PET). Revista Clínica Española. 207(11). 541–547. 6 indexed citations
18.
Cortez, Paulo, Miguel Rio, Miguel Rocha, & Pedro Sousa. (2006). Internet Trafc Forecasting using Neural Networks. 1 indexed citations
19.
Rio, Miguel, et al.. (2005). Miositis osificante progresiva. Utilidad de la gammagrafía ósea. Revista Española de Medicina Nuclear. 24(3). 195–198. 1 indexed citations
20.
Torres, M.D. Martínez del Valle, et al.. (2004). Valor de la SPECT con Talio-201 en la tipificación de lesiones ocupantes de espacio intracerebrales. Revista Española de Medicina Nuclear. 23(5). 330–337. 4 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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