Alfredo Núñez

4.5k total citations · 2 hit papers
130 papers, 3.4k citations indexed

About

Alfredo Núñez is a scholar working on Mechanical Engineering, Civil and Structural Engineering and Control and Systems Engineering. According to data from OpenAlex, Alfredo Núñez has authored 130 papers receiving a total of 3.4k indexed citations (citations by other indexed papers that have themselves been cited), including 62 papers in Mechanical Engineering, 39 papers in Civil and Structural Engineering and 35 papers in Control and Systems Engineering. Recurrent topics in Alfredo Núñez's work include Railway Engineering and Dynamics (53 papers), Structural Health Monitoring Techniques (21 papers) and Railway Systems and Energy Efficiency (19 papers). Alfredo Núñez is often cited by papers focused on Railway Engineering and Dynamics (53 papers), Structural Health Monitoring Techniques (21 papers) and Railway Systems and Energy Efficiency (19 papers). Alfredo Núñez collaborates with scholars based in Netherlands, Chile and China. Alfredo Núñez's co-authors include Rolf Dollevoet, Zili Li, Bart De Schutter, Hongrui Wang, Doris Sáez, Zhigang Liu, M. Molodova, Cristián E. Cortés, Siamak Hajizadeh and Zhiwei Han and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Industrial Electronics and Applied Energy.

In The Last Decade

Alfredo Núñez

123 papers receiving 3.3k 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.

Automatic Defect Detection of Fasteners on the Catenary Support Device Using Deep Convolutional Neural Network

2017 359 citations Junwen Chen, Zhigang Liu et al. IEEE Transactions on Instrumentation and Measurement profile →
Deep convolutional neural networks for detection of rail surface defects

2016 253 citations Siamak Hajizadeh, Alfredo Núñez et al. Research Repository (Delft University of Technology) profile →

Peers

Countries citing papers authored by Alfredo Núñez

Since Specialization

Citations

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

Fields of papers citing papers by Alfredo Núñez

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alfredo Núñez

This figure shows the co-authorship network connecting the top 25 collaborators of Alfredo Núñez. A scholar is included among the top collaborators of Alfredo Núñez 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 Alfredo Núñez. Alfredo Núñez 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	Spiking neural network with time-varying weights for rail squat detection 2025 ·Applied Soft Computing ·(unknown), (unknown), Zili Li, Alfredo Núñez	0
2	Neural Differential Equation-Based Two-Stage Approach for Generalization of Beam Dynamics 2024 ·IEEE Transactions on Industrial Informatics ·(unknown), Hongrui Wang, (unknown), K. El Sayed, Alfredo Núñez, Daniel M. Tartakovsky, Rolf Dollevoet	2
3	Vertical dynamic measurements of a railway transition zone: a case study in Sweden 2024 ·Journal of Civil Structural Health Monitoring ·(unknown), Chen Shen, (unknown), Li Wang, Alfredo Núñez, Zili Li	3
4	Transfer learning for improved generalizability in causal physics-informed neural networks for beam simulations 2024 ·Engineering Applications of Artificial Intelligence ·(unknown), Hongrui Wang, Alfredo Núñez, Rolf Dollevoet	23
5	INCORPORATING MODAL TESTING INTO DYNAMIC LOAD IDENTIFICATION FROM STRUCTURAL VIBRATION MEASUREMENT 2023 ·(unknown), Alfredo Núñez, Zili Li	0
6	Physics-Informed Neural Networks for Solving Forward and Inverse Problems in Complex Beam Systems 2023 ·IEEE Transactions on Neural Networks and Learning Systems ·(unknown), Hongrui Wang, Alfredo Núñez, Rolf Dollevoet	61
7	Microgrid planning based on computational intelligence methods for rural communities: A case study in the José Painecura Mapuche community, Chile 2023 ·Expert Systems with Applications ·(unknown), Luis G. Marín, (unknown), (unknown), Doris Sáez, Alfredo Núñez	4
8	Rail wear rate on the Belgian railway network – a big-data analysis 2023 ·International Journal of Rail Transportation ·(unknown), Li Wang, Alfredo Núñez, Rolf Dollevoet, Zili Li	5
9	An Interpretable Method for Operational Modal Analysis in Time-Frequency Representation and Its Applications to Railway Sleepers 2023 ·Structural Control and Health Monitoring ·(unknown), Chen Shen, Alfredo Núñez, Rolf Dollevoet, Weihua Zhang, Zili Li	8
10	A Looseness Detection Method for Railway Catenary Fasteners Based on Reinforcement Learning Refined Localization 2021 ·IEEE Transactions on Instrumentation and Measurement ·Junping Zhong, Zhigang Liu, Hongrui Wang, Wenqiang Liu, Cheng Yang, Zhiwei Han, Alfredo Núñez	28
11	Unified Deep Learning Architecture for the Detection of All Catenary Support Components 2020 ·IEEE Access ·Wenqiang Liu, Zhigang Liu, Alfredo Núñez, Zhiwei Han	22
12	High-Precision Detection Method for Structure Parameters of Catenary Cantilever Devices Using 3-D Point Cloud Data 2020 ·IEEE Transactions on Instrumentation and Measurement ·Wenqiang Liu, Zhigang Liu, (unknown), Zhiwei Han, Alfredo Núñez	12
13	Multimodal dispersive waves in a free rail: Numerical modeling and experimental investigation 2020 ·Mechanical Systems and Signal Processing ·Pan Zhang, Shaoguang Li, Alfredo Núñez, Zili Li	26
14	A Bayesian Network Approach for Condition Monitoring of High-Speed Railway Catenaries 2019 ·IEEE Transactions on Intelligent Transportation Systems ·Hongrui Wang, Alfredo Núñez, Zhigang Liu, Dongliang Zhang, Rolf Dollevoet	35
15	Identification of distributed-parameter systems from sparse measurements 2017 ·Applied Mathematical Modelling ·(unknown), Robert Babuška, Alfredo Núñez, Bart De Schutter	9
16	Automatic Defect Detection of Fasteners on the Catenary Support Device Using Deep Convolutional Neural Network breakdown → 2017 ·IEEE Transactions on Instrumentation and Measurement ·Junwen Chen, Zhigang Liu, Hongrui Wang, Alfredo Núñez, Zhiwei Han	359
17	Deep convolutional neural networks for detection of rail surface defects breakdown → 2016 ·Research Repository (Delft University of Technology) ·(unknown), Siamak Hajizadeh, Alfredo Núñez, Robert Babuška, Bart De Schutter	253
18	Maintenance decision indicators for treating squats in railway infrastructures 2015 ·Research Repository (Delft University of Technology) ·Ali Ashraf Jamshidi, Alfredo Núñez, Zili Li	4
19	Monitoring the railway infrastructure: Detection of surface defects using wavelets 2013 ·M. Molodova, Zili Li, Alfredo Núñez, Rolf Dollevoet	18
20	Fuzzy-model-based hybrid predictive control 2008 ·ISA Transactions ·Alfredo Núñez, Doris Sáez, (unknown), Igor Škrjanc	23

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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