Leaderboards/Structural Health Monitoring Techniques

Structural Health Monitoring Techniques

Last updated July 7, 2026

Rising Stars

New and hot

Rising Stars Researchers

1
Vilhjálmur Ásgeirsson
University of Iceland
2
Furkan Luleci
University of Central Florida
3
Anthony Massari
California Institute of Technology
4
Hoang-Le Minh
Ho Chi Minh City Open University
5
Changqi Luo
University of Electronic Science and Technology of China
6
Miaofen Li
Xidian University
7
Valentina Giglioni
University of Perugia
8
Antonios Kamariotis
ETH Zurich
9
Hyogu Jeong
Queensland University of Technology
10
Maliki Moustapha
ETH Zurich

Rising Stars Papers

1
Active Kriging-based conjugate first-order reliability method for highly efficient structural reliability analysis using resample strategy
Computer Methods in Applied Mechanics and Engineering|2024
103 cit.
2
A domain adaptation approach to damage classification with an application to bridge monitoring
Mechanical Systems and Signal Processing|2024
73 cit.
3
Transfer learning in bridge monitoring: Laboratory study on domain adaptation for population-based SHM of multispan continuous girder bridges
Mechanical Systems and Signal Processing|2024
47 cit.
4
Reliability analysis of arbitrary systems based on active learning and global sensitivity analysis
Reliability Engineering & System Safety|2024
34 cit.
5
An advanced physics-informed neural network-based framework for nonlinear and complex topology optimization
Engineering Structures|2024
26 cit.
6
Fusing infrastructure health monitoring data in point cloud
Automation in Construction|2024
23 cit.
7
Uniform importance sampling with rejection control for structural reliability analysis
Computer Methods in Applied Mechanics and Engineering|2024
18 cit.
8
Bringing site to the office: Decision-making in infrastructure management through virtual reality
Automation in Construction|2024
13 cit.
9
Community Twin Ecosystem for Disaster Resilient Communities
Smart Cities|2024
11 cit.
10
On the Consistent Classification and Treatment of Uncertainties in Structural Health Monitoring Applications
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B Mechanical Engineering|2024
10 cit.

Emerging Leaders

Gaining momentum

Emerging Leaders Researchers

1
Yasutaka Narazaki
Zhejiang University
2
Ole Øiseth
Norwegian University of Science and Technology
3
Antônio Carlos Ancelotti
Universidade Federal de Itajubá
4
Shing Shin Cheng
Chinese University of Hong Kong
5
Samir Khatir
Ho Chi Minh City Open University
6
Wael A. Altabey
Alexandria University
7
Juan P. Amézquita-Sánchez
Autonomous University of Queretaro
8
Stephanie German Paal
Mitchell Institute
9
Jiangpeng Shu
Zhejiang University
10
Honglan Huang
PLA Rocket Force University of Engineering

Emerging Leaders Papers

1
Crack detection and quantification for concrete structures using UAV and transformer
Automation in Construction|2023
200 cit.
2
Vision-based navigation planning for autonomous post-earthquake inspection of reinforced concrete railway viaducts using unmanned aerial vehicles
Automation in Construction|2022
82 cit.
3
Automatic pixel‐level crack detection and evaluation of concrete structures using deep learning
Structural Control and Health Monitoring|2022
74 cit.
4
A data-driven structural damage identification approach using deep convolutional-attention-recurrent neural architecture under temperature variations
Engineering Structures|2022
72 cit.
5
Mass tuning technique for a broadband piezoelectric energy harvester array
Mechanical Systems and Signal Processing|2022
62 cit.
6
Seismic response prediction of structures based on Runge-Kutta recurrent neural network with prior knowledge
Engineering Structures|2023
59 cit.
7
Active Client Selection for Clustered Federated Learning
IEEE Transactions on Neural Networks and Learning Systems|2023
59 cit.
8
Vortex-induced vibration control of a flexible circular cylinder using a nonlinear energy sink
Journal of Wind Engineering and Industrial Aerodynamics|2022
55 cit.
9
Point cloud-based dimensional quality assessment of precast concrete components using deep learning
Journal of Building Engineering|2023
55 cit.
10
Artificial intelligence-enhanced seismic response prediction of reinforced concrete frames
Advanced Engineering Informatics|2022
53 cit.

Current Senior Leaders

Established & currently active

Current Senior Leaders Researchers

1
James L. Beck
California Institute of Technology
2
Daniel J. Inman
University of Michigan
3
C. Allin Cornell
Stanford University
4
Norden E. Huang
National Central University
5
Guido De Roeck
KU Leuven
6
Dominique Zosso
Montana State University
7
Gangbing Song
University of Houston
8
Hojjat Adeli
The Ohio State University
9
Oral Büyüköztürk
Massachusetts Institute of Technology
10
Hui Li
Los Alamos National Laboratory

Current Senior Leaders Papers

1
The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis
Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences|1998
23.3k cit.
2
Variational Mode Decomposition
IEEE Transactions on Signal Processing|2014
8.6k cit.
3
ENSEMBLE EMPIRICAL MODE DECOMPOSITION: A NOISE-ASSISTED DATA ANALYSIS METHOD
Advances in Adaptive Data Analysis|2008
8.6k cit.
4
Incremental dynamic analysis
Earthquake Engineering & Structural Dynamics|2001
4.1k cit.
5
Engineering seismic risk analysis
Bulletin of the Seismological Society of America|1968
3.8k cit.
6
Deep Learning‐Based Crack Damage Detection Using Convolutional Neural Networks
Computer-Aided Civil and Infrastructure Engineering|2017
3.1k cit.
7
1D convolutional neural networks and applications: A survey
Qatar University QSpace (Qatar University)|2022
2.7k cit.
8
Estimation of small failure probabilities in high dimensions by subset simulation
Probabilistic Engineering Mechanics|2001
2.4k cit.
9
Probabilistic Basis for 2000 SAC Federal Emergency Management Agency Steel Moment Frame Guidelines
Journal of Structural Engineering|2002
2.2k cit.
10
A NEW VIEW OF NONLINEAR WATER WAVES: The Hilbert Spectrum
Annual Review of Fluid Mechanics|1999
2.1k cit.

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