Manuel Díáz

4.1k total citations · 2 hit papers
107 papers, 2.5k citations indexed

About

Manuel Díáz is a scholar working on Computer Networks and Communications, Hardware and Architecture and Artificial Intelligence. According to data from OpenAlex, Manuel Díáz has authored 107 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 68 papers in Computer Networks and Communications, 25 papers in Hardware and Architecture and 21 papers in Artificial Intelligence. Recurrent topics in Manuel Díáz's work include Energy Efficient Wireless Sensor Networks (24 papers), Distributed systems and fault tolerance (21 papers) and Real-Time Systems Scheduling (20 papers). Manuel Díáz is often cited by papers focused on Energy Efficient Wireless Sensor Networks (24 papers), Distributed systems and fault tolerance (21 papers) and Real-Time Systems Scheduling (20 papers). Manuel Díáz collaborates with scholars based in Spain, Germany and United States. Manuel Díáz's co-authors include Cristian Martín, Jaime Chen, Bartolomé Rubio, Enrique Soler, Ana Reyna, Luis Llopis, José M. Troya, José A. Dianes, Peter Langendöerfer and Augusto Casaca and has published in prestigious journals such as IEEE Access, Sensors and IEEE Transactions on Industrial Informatics.

In The Last Decade

Manuel Díáz

98 papers receiving 2.4k citations

Hit Papers

On blockchain and its integration with IoT. Challenges an... 2016 2026 2019 2022 2018 2016 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Manuel Díáz Spain 17 1.5k 1.4k 378 312 266 107 2.5k
Adel N. Toosi Australia 29 2.0k 1.4× 1.7k 1.3× 587 1.6× 305 1.0× 228 0.9× 72 2.9k
Christos Stergiou Greece 18 1.2k 0.8× 849 0.6× 581 1.5× 406 1.3× 291 1.1× 37 2.3k
Walter de Donato Italy 12 2.2k 1.4× 1.2k 0.9× 530 1.4× 448 1.4× 316 1.2× 23 2.7k
Herodotos Herodotou Cyprus 19 1.1k 0.7× 1.1k 0.8× 423 1.1× 487 1.6× 221 0.8× 77 2.2k
Nicola Dragoni Denmark 23 1.6k 1.1× 1.0k 0.7× 661 1.7× 516 1.7× 177 0.7× 106 2.5k
Jie Xu United Kingdom 26 1.9k 1.3× 1.6k 1.1× 503 1.3× 289 0.9× 204 0.8× 150 2.7k
Wenny Rahayu Australia 29 2.0k 1.3× 1.3k 0.9× 1.0k 2.7× 564 1.8× 429 1.6× 156 3.6k
Jules White United States 26 1.0k 0.7× 1.5k 1.1× 1.0k 2.8× 218 0.7× 281 1.1× 127 3.0k
Fan Liang United States 16 1.2k 0.8× 766 0.6× 589 1.6× 464 1.5× 260 1.0× 46 2.2k
Francesco Longo Italy 24 1.8k 1.2× 1.4k 1.0× 271 0.7× 348 1.1× 315 1.2× 125 2.4k

Countries citing papers authored by Manuel Díáz

Since Specialization
Citations

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

Fields of papers citing papers by Manuel Díáz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Manuel Díáz

This figure shows the co-authorship network connecting the top 25 collaborators of Manuel Díáz. A scholar is included among the top collaborators of Manuel Díáz 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 Manuel Díáz. Manuel Díáz 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.
Martín, Cristian, et al.. (2025). A soft sensor open-source methodology for inexpensive monitoring of water quality: A case study of NO3− concentrations. Journal of Computational Science. 85. 102522–102522. 4 indexed citations
2.
Martín, Cristian, et al.. (2024). Online learning and continuous model upgrading with data streams through the Kafka-ML framework. Future Generation Computer Systems. 160. 251–263. 3 indexed citations
3.
Martín, Cristian, Bartolomé Rubio, Manuel Díáz, et al.. (2024). Integrating FMI and ML/AI models on the open‐source digital twin framework OpenTwins. Software Practice and Experience. 54(8). 1470–1490. 3 indexed citations
4.
Martín, Cristian, et al.. (2024). Distributed digital twins on the open-source OpenTwins framework. Advanced Engineering Informatics. 64. 102970–102970. 4 indexed citations
5.
Martín, Cristian, et al.. (2024). Towards flexible data stream collaboration: Federated Learning in Kafka-ML. Internet of Things. 25. 101036–101036. 7 indexed citations
6.
Rubio, Bartolomé, et al.. (2024). Functions as a service for distributed deep neural network inference over the cloud‐to‐things continuum. Software Practice and Experience. 54(8). 1297–1311.
7.
Martín, Cristian, Luis Llopis, Manuel Díáz, et al.. (2023). Pollen recognition through an open-source web-based system: automated particle counting for aerobiological analysis. Earth Science Informatics. 17(1). 699–710.
8.
Martín, Cristian, et al.. (2023). OpenTwins: An open-source framework for the development of next-gen compositional digital twins. Computers in Industry. 152. 104007–104007. 44 indexed citations
9.
Martín, Cristian, et al.. (2023). Portable motorized telescope system for wind turbine blades damage detection. Engineering Reports. 7(1). 10 indexed citations
10.
Martín, Cristian, et al.. (2023). Maintaining flexibility in smart grid consumption through deep learning and deep reinforcement learning. Energy and AI. 13. 100241–100241. 20 indexed citations
11.
Martín, Cristian, et al.. (2021). Facilitating the monitoring and management of structural health in civil infrastructures with an Edge/Fog/Cloud architecture. Computer Standards & Interfaces. 81. 103600–103600. 30 indexed citations
12.
Martín, Cristian, et al.. (2021). Kafka-ML: Connecting the data stream with ML/AI frameworks. Repositorio Institucional de la Universidad de Málaga (University of Málaga). 40 indexed citations
13.
Martín, Cristian, et al.. (2021). An open source framework based on Kafka-ML for Distributed DNN inference over the Cloud-to-Things continuum. Journal of Systems Architecture. 118. 102214–102214. 22 indexed citations
14.
Martín, Cristian, et al.. (2021). Managing and Deploying Distributed and Deep Neural Models Through Kafka-ML in the Cloud-to-Things Continuum. IEEE Access. 9. 125478–125495. 9 indexed citations
15.
Martín, Cristian, Jeroen Hoebeke, Jen Rossey, et al.. (2018). Appdaptivity: An Internet of Things Device-Decoupled System for Portable Applications in Changing Contexts. Sensors. 18(5). 1345–1345. 4 indexed citations
16.
Conde‐Ruiz, J. Ignacio, et al.. (2016). Sanidad, Educación y Protección Social: Recortes Durante la Crisis. RePEc: Research Papers in Economics. 2 indexed citations
17.
Díáz, Manuel, et al.. (2011). Coalitions and Incentives for Content Distribution over a Secure Peer-to-Peer Middleware. 71–78. 1 indexed citations
18.
Díáz, Manuel, et al.. (2004). Integrating real-time analysis in a component model for embedded systems. 14–21. 12 indexed citations
19.
Díáz, Manuel, Bartolomé Rubio, Enrique Soler, & José M. Troya. (2003). Domain interaction patterns to coordinate HPF tasks. Parallel Computing. 29(7). 925–951. 4 indexed citations
20.
Díáz, Manuel, Ernesto Pimentel, & José M. Troya. (1992). A Declarative Environment for Distributed Programming. 163–169. 2 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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