Manuel López‐Martín

2.3k total citations · 1 hit paper
26 papers, 1.6k citations indexed

About

Manuel López‐Martín is a scholar working on Artificial Intelligence, Computer Networks and Communications and Statistical and Nonlinear Physics. According to data from OpenAlex, Manuel López‐Martín has authored 26 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 11 papers in Computer Networks and Communications and 7 papers in Statistical and Nonlinear Physics. Recurrent topics in Manuel López‐Martín's work include Network Security and Intrusion Detection (11 papers), Anomaly Detection Techniques and Applications (8 papers) and Internet Traffic Analysis and Secure E-voting (6 papers). Manuel López‐Martín is often cited by papers focused on Network Security and Intrusion Detection (11 papers), Anomaly Detection Techniques and Applications (8 papers) and Internet Traffic Analysis and Secure E-voting (6 papers). Manuel López‐Martín collaborates with scholars based in Spain, United Kingdom and Belgium. Manuel López‐Martín's co-authors include Belén Carro, Antonio Sánchez-Esguevillas, Jaime Lloret, Juan Ignacio Arribas, Soledad Le Clainche, Ángel Nevado, Jose Perez, Luís Hernández-Callejo, Iain E. G. Richardson and M. Bystrom and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and IEEE Communications Magazine.

In The Last Decade

Manuel López‐Martín

25 papers receiving 1.5k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Network Traffic Classifier With Convolutional and Recurrent Neural Networks for Internet of Things

2017 504 citations Manuel López‐Martín, Belén Carro et al. IEEE Access profile →

Peers

Countries citing papers authored by Manuel López‐Martín

Since Specialization

Citations

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

Fields of papers citing papers by Manuel López‐Martín

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Manuel López‐Martín

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

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	Generalization capabilities and robustness of hybrid models grounded in physics compared to purely deep learning models 2025 ·Physics of Fluids ·(unknown), (unknown), Manuel López‐Martín, Soledad Le Clainche	2
2	ModelFLOWs-app: Data-driven post-processing and reduced order modelling tools 2024 ·Computer Physics Communications ·(unknown), (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), Manuel López‐Martín, Soledad Le Clainche	7
3	Deep learning combined with singular value decomposition to reconstruct databases in fluid dynamics 2023 ·Expert Systems with Applications ·(unknown), (unknown), Manuel López‐Martín, Soledad Le Clainche	10
4	Forecasting through deep learning and modal decomposition in two-phase concentric jets 2023 ·Expert Systems with Applications ·(unknown), (unknown), Manuel López‐Martín, Jose Perez, Soledad Le Clainche	5
5	Contrastive Learning Over Random Fourier Features for IoT Network Intrusion Detection 2022 ·IEEE Internet of Things Journal ·Manuel López‐Martín, Antonio Sánchez-Esguevillas, Juan Ignacio Arribas, Belén Carro	10
6	Novel Data-Driven Models Applied to Short-Term Electric Load Forecasting 2021 ·Applied Sciences ·Manuel López‐Martín, Antonio Sánchez-Esguevillas, Luís Hernández-Callejo, Juan Ignacio Arribas, Belén Carro	20
7	Network intrusion detection with a novel hierarchy of distances between embeddings of hash IP addresses 2021 ·Knowledge-Based Systems ·Manuel López‐Martín, Belén Carro, Juan Ignacio Arribas, Antonio Sánchez-Esguevillas	23
8	Additive Ensemble Neural Network with Constrained Weighted Quantile Loss for Probabilistic Electric-Load Forecasting 2021 ·Sensors ·Manuel López‐Martín, Antonio Sánchez-Esguevillas, Luís Hernández-Callejo, Juan Ignacio Arribas, Belén Carro	15
9	Network Intrusion Detection Based on Extended RBF Neural Network With Offline Reinforcement Learning 2021 ·IEEE Access ·Manuel López‐Martín, Antonio Sánchez-Esguevillas, Juan Ignacio Arribas, Belén Carro	48
10	A predictive hybrid reduced order model based on proper orthogonal decomposition combined with deep learning architectures 2021 ·Expert Systems with Applications ·(unknown), Manuel López‐Martín, Belén Carro, Juan Ignacio Arribas, Jose Perez, Soledad Le Clainche	47
11	Model-free short-term fluid dynamics estimator with a deep 3D-convolutional neural network 2021 ·Expert Systems with Applications ·Manuel López‐Martín, Soledad Le Clainche, Belén Carro	28
12	Detection of early stages of Alzheimer’s disease based on MEG activity with a randomized convolutional neural network 2020 ·Artificial Intelligence in Medicine ·Manuel López‐Martín, Ángel Nevado, Belén Carro	41
13	Adversarial environment reinforcement learning algorithm for intrusion detection 2019 ·Computer Networks ·(unknown), Manuel López‐Martín, Belén Carro	148
14	Shallow neural network with kernel approximation for prediction problems in highly demanding data networks 2019 ·Expert Systems with Applications ·Manuel López‐Martín, Belén Carro, Antonio Sánchez-Esguevillas, Jaime Lloret	60
15	Application of deep reinforcement learning to intrusion detection for supervised problems 2019 ·Expert Systems with Applications ·Manuel López‐Martín, Belén Carro, Antonio Sánchez-Esguevillas	222
16	Neural network architecture based on gradient boosting for IoT traffic prediction 2019 ·Future Generation Computer Systems ·Manuel López‐Martín, Belén Carro, Antonio Sánchez-Esguevillas	36
17	Variational data generative model for intrusion detection 2018 ·Knowledge and Information Systems ·Manuel López‐Martín, Belén Carro, Antonio Sánchez-Esguevillas	33
18	Deep Learning Model for Multimedia Quality of Experience Prediction Based on Network Flow Packets 2018 ·IEEE Communications Magazine ·Manuel López‐Martín, Belén Carro, Jaime Lloret, (unknown), Antonio Sánchez-Esguevillas	39
19	Conditional Variational Autoencoder for Prediction and Feature Recovery Applied to Intrusion Detection in IoT 2017 ·Sensors ·Manuel López‐Martín, Belén Carro, Antonio Sánchez-Esguevillas, Jaime Lloret	196
20	DYNAMIC CONFIGURATION: BEYOND VIDEO CODING STANDARDS 2010 ·Iain E. G. Richardson, M. Bystrom, (unknown), Manuel López‐Martín	2

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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