Fernando Terroso-Sáenz

1.1k total citations
53 papers, 809 citations indexed

About

Fernando Terroso-Sáenz is a scholar working on Transportation, Building and Construction and Signal Processing. According to data from OpenAlex, Fernando Terroso-Sáenz has authored 53 papers receiving a total of 809 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Transportation, 17 papers in Building and Construction and 16 papers in Signal Processing. Recurrent topics in Fernando Terroso-Sáenz's work include Human Mobility and Location-Based Analysis (23 papers), Traffic Prediction and Management Techniques (13 papers) and Data Management and Algorithms (12 papers). Fernando Terroso-Sáenz is often cited by papers focused on Human Mobility and Location-Based Analysis (23 papers), Traffic Prediction and Management Techniques (13 papers) and Data Management and Algorithms (12 papers). Fernando Terroso-Sáenz collaborates with scholars based in Spain, Austria and France. Fernando Terroso-Sáenz's co-authors include Antonio Skármeta, Aurora González-Vidal, Mercedes Valdés-Vela, Alfonso P. Ramallo-González, Andrés Muñoz, M. Victoria Moreno, R. Toledo-Moreo, Miguel A. Zamora, Victor Chang and José M. Cecilia and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and Sensors.

In The Last Decade

Fernando Terroso-Sáenz

51 papers receiving 777 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Fernando Terroso-Sáenz Spain 15 239 212 204 185 116 53 809
Azizur Rahim China 13 203 0.8× 376 1.8× 153 0.8× 265 1.4× 69 0.6× 25 833
M. Victoria Moreno Spain 16 372 1.6× 337 1.6× 195 1.0× 64 0.3× 150 1.3× 35 946
Ajay Vikram Singh India 14 139 0.6× 224 1.1× 62 0.3× 110 0.6× 82 0.7× 74 615
Hyuncheol Seo South Korea 14 180 0.8× 244 1.2× 218 1.1× 71 0.4× 144 1.2× 30 887
Wei-Hsun Lee Taiwan 13 172 0.7× 103 0.5× 298 1.5× 218 1.2× 51 0.4× 29 693
Saleh M. Altowaijri Saudi Arabia 13 132 0.6× 223 1.1× 89 0.4× 94 0.5× 89 0.8× 32 592
Alex Gluhak United Kingdom 9 313 1.3× 520 2.5× 101 0.5× 99 0.5× 163 1.4× 18 902
Pablo Sotres Spain 13 280 1.2× 536 2.5× 136 0.7× 152 0.8× 159 1.4× 26 955
Azedine Boulmakoul Morocco 13 70 0.3× 126 0.6× 141 0.7× 157 0.8× 48 0.4× 62 680

Countries citing papers authored by Fernando Terroso-Sáenz

Since Specialization
Citations

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

Fields of papers citing papers by Fernando Terroso-Sáenz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fernando Terroso-Sáenz. 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 Fernando Terroso-Sáenz. The network helps show where Fernando Terroso-Sáenz may publish in the future.

Co-authorship network of co-authors of Fernando Terroso-Sáenz

This figure shows the co-authorship network connecting the top 25 collaborators of Fernando Terroso-Sáenz. A scholar is included among the top collaborators of Fernando Terroso-Sáenz 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 Fernando Terroso-Sáenz. Fernando Terroso-Sáenz 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.
Muñoz, Andrés, et al.. (2025). Exploiting synthetic data generation to enhance pollution prediction. Applied Soft Computing. 175. 113076–113076. 1 indexed citations
2.
Navarro, Pedro, et al.. (2025). MUSYNERGY: A framework for music collaboration discovery based on neural networks and graph analysis. Entertainment Computing. 55. 101033–101033.
3.
Terroso-Sáenz, Fernando, J. Soto, Andrés Muñoz, & Philippe Roose. (2025). PRESTO: A Recommender of Musical Collaborations Based on Heterogeneous Graph Neural Networks. International Journal of Interactive Multimedia and Artificial Intelligence. 9(6). 28–37. 1 indexed citations
4.
Terroso-Sáenz, Fernando, et al.. (2024). Developing Time Series Forecasting Models with Generative Large Language Models. ACM Transactions on Intelligent Systems and Technology. 16(6). 1–12. 2 indexed citations
5.
Bueno-Crespo, Andrés, et al.. (2023). Evaluation of synthetic data generation for intelligent climate control in greenhouses. Applied Intelligence. 53(21). 24765–24781. 11 indexed citations
6.
Terroso-Sáenz, Fernando, J. Soto, & Andrés Muñoz. (2023). Music Mobility Patterns: How Songs Propagate Around The World Through Spotify. Pattern Recognition. 143. 109807–109807. 4 indexed citations
7.
Terroso-Sáenz, Fernando, et al.. (2023). A multi-model deep learning approach to address prediction imbalances in smart greenhouses. Computers and Electronics in Agriculture. 216. 108537–108537. 8 indexed citations
8.
Terroso-Sáenz, Fernando, et al.. (2023). Beach and Weather: A Mobile Crowdsensing platform to report beach conditions. Software Impacts. 15. 100472–100472. 2 indexed citations
9.
Terroso-Sáenz, Fernando, et al.. (2022). An analysis of twitter as a relevant human mobility proxy. GeoInformatica. 26(4). 677–706. 11 indexed citations
10.
Terroso-Sáenz, Fernando & Andrés Muñoz. (2021). Nation-wide human mobility prediction based on graph neural networks. Applied Intelligence. 52(4). 4144–4160. 14 indexed citations
11.
Terroso-Sáenz, Fernando, et al.. (2021). Human Mobility Prediction With Region-Based Flows and Water Consumption. IEEE Access. 9. 88651–88663. 7 indexed citations
12.
13.
Terroso-Sáenz, Fernando, Andrés Muñoz, & José M. Cecilia. (2019). QUADRIVEN: A Framework for Qualitative Taxi Demand Prediction Based on Time-Variant Online Social Network Data Analysis. Sensors. 19(22). 4882–4882. 8 indexed citations
14.
Fotopoulou, Eleni, Anastasios Zafeiropoulos, Fernando Terroso-Sáenz, et al.. (2017). Providing Personalized Energy Management and Awareness Services for Energy Efficiency in Smart Buildings. Sensors. 17(9). 2054–2054. 49 indexed citations
15.
Terroso-Sáenz, Fernando, Aurora González-Vidal, & Antonio Skármeta. (2016). Towards anticipate detection of complex event processing rules with probabilistic modelling. International Journal of Design & Nature and Ecodynamics. 11(3). 275–283. 1 indexed citations
16.
Terroso-Sáenz, Fernando, Mercedes Valdés-Vela, Aurora González-Vidal, & Antonio Skármeta. (2016). Human Mobility Modelling Based on Dense Transit Areas Detection with Opportunistic Sensing. Mobile Information Systems. 2016. 1–15. 3 indexed citations
17.
Terroso-Sáenz, Fernando, et al.. (2015). CEP-traj: An event-based solution to process trajectory data. Information Systems. 52. 34–54. 12 indexed citations
18.
Terroso-Sáenz, Fernando, Mercedes Valdés-Vela, & Antonio Skármeta. (2015). Towards human mobility extraction based on social media with Complex Event Processing. 55. 435–440. 3 indexed citations
19.
Terroso-Sáenz, Fernando, Mercedes Valdés-Vela, & Antonio Skármeta. (2015). A complex event processing approach to detect abnormal behaviours in the marine environment. Information Systems Frontiers. 18(4). 765–780. 22 indexed citations
20.
Terroso-Sáenz, Fernando, Mercedes Valdés-Vela, & Antonio Skármeta. (2014). Design of an Event-based architecture for the intra-vehicular context perception. International Conference on Information Fusion. 1–7. 1 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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