World's Best Scientists 2026 revealed!
Ka-Veng Yuen

Ka-Veng Yuen

D-Index & Metrics

Engineering and Technology

D-Index
56
Citations
10928
World Ranking
2846
National Ranking
571

Overview

Ka-Veng Yuen is affiliated with the University of Macau in China. Their research primarily focuses on engineering, with a significant emphasis on civil and structural engineering. Their work also spans control and systems engineering, statistics, probability and uncertainty, mechanical engineering, and mechanics of materials.

The scientist's publication record includes numerous papers in well-known journals and conferences, focusing on key topics such as structural health monitoring techniques, infrastructure maintenance and monitoring, probabilistic and robust engineering design, ultrasonics and acoustic wave propagation, non-destructive testing techniques, concrete corrosion and durability, and fault detection and control systems.

Recent papers authored or co-authored by Ka-Veng Yuen include:

  • "A Model-Driven Scheme to Compensate the Strain-Based Non-Intrusive Dynamic Pressure Measurement for Hydraulic Pipe" (2021) published in IEEE Transactions on Instrumentation and Measurement
  • "Crack detection using fusion features-based broad learning system and image processing" (2021) published in Computer-Aided Civil and Infrastructure Engineering
  • "Ensemble learning-based structural health monitoring by Mahalanobis distance metrics" (2020) published in Structural Control and Health Monitoring
  • "Early damage detection by an innovative unsupervised learning method based on kernel null space and peak-over-threshold" (2021) published in Computer-Aided Civil and Infrastructure Engineering
  • "Review of artificial intelligence-based bridge damage detection" (2022) published in Advances in Mechanical Engineering

Ka-Veng Yuen frequently publishes in the following venues:

  • Mechanical Systems and Signal Processing
  • Structural Control and Health Monitoring
  • Computer-Aided Civil and Infrastructure Engineering
  • Engineering Structures
  • SSRN Electronic Journal

Collaborative efforts include frequent co-authorship with researchers such as Wang-Ji Yan, Sin-Chi Kuok, Michael Beer, and Costas Papadimitriou. Among these, Wang-Ji Yan appears most often, indicating an ongoing research partnership.

The scientist's research contributions cover a broad spectrum within engineering, with 235 publications categorized under the broader field. Subfield concentrations include 131 publications in civil and structural engineering and 30 in control and systems engineering, among others.

Best Publications

  • Bayesian Methods for Structural Dynamics and Civil Engineering

    Ka-Veng Yuen

  • Model Selection using Response Measurements: Bayesian Probabilistic Approach

    James L. Beck;Ka-Veng Yuen

  • A Model-Driven Scheme to Compensate the Strain-Based Non-Intrusive Dynamic Pressure Measurement for Hydraulic Pipe

    Zechao Wang;Mingyao Liu;Wang-Ji Yan;Han Song

  • Overview of Environment Perception for Intelligent Vehicles

    Hao Zhu;Ka-Veng Yuen;Lyudmila Mihaylova;Henry Leung

  • Bayesian spectral density approach for modal updating using ambient data

    Lambros S. Katafygiotis;Ka-Veng Yuen

  • Efficient model updating and health monitoring methodology using incomplete modal data without mode matching

    Ka-Veng Yuen;James L. Beck;Lambros S. Katafygiotis

  • Bayesian Fast Fourier Transform Approach for Modal Updating Using Ambient Data

    Ka-Veng Yuen;Lambros S. Katafygiotis

  • Recent developments of Bayesian model class selection and applications in civil engineering

    Ka-Veng Yuen

  • Bayesian Methods for Updating Dynamic Models

    Ka-Veng Yuen;Sin-Chi Kuok

  • Bayesian time–domain approach for modal updating using ambient data

    Ka-Veng Yuen;Lambros S Katafygiotis

  • Ambient interference in long-term monitoring of buildings

    Ka-Veng Yuen;Sin-Chi Kuok

  • Two-Stage Structural Health Monitoring Approach for Phase I Benchmark Studies

    Ka-Veng Yuen;Siu Kui Au;James L. Beck

  • Real-Time System Identification: An Algorithm for Simultaneous Model Class Selection and Parametric Identification

    Ka-Veng Yuen;He-Qing Mu

  • Structural Health Monitoring via Measured Ritz Vectors Utilizing Artificial Neural Networks

    Heung-Fai Lam;Ka-Veng Yuen;James L. Beck

  • Reliability analysis of soil-water characteristics curve and its application to slope stability analysis

    C.F. Chiu;W.M. Yan;Ka-Veng Yuen

  • Vibration-based damage detection for structural connections using incomplete modal data by Bayesian approach and model reduction technique

    Tao Yin;Qing-Hui Jiang;Ka-Veng Yuen

  • On the complexity of artificial neural networks for smart structures monitoring

    Ka-Veng Yuen;Heung-Fai Lam

  • Efficient Bayesian sensor placement algorithm for structural identification: a general approach for multi‐type sensory systems

    Ka-Veng Yuen;Sin-Chi Kuok

  • Review of artificial intelligence-based bridge damage detection

    Unknown

  • Crack detection using fusion features-based broad learning system and image processing

    Yang Zhang;Yang Zhang;Ka-Veng Yuen

  • Substructure Identification and Health Monitoring Using Noisy Response Measurements Only

    Ka-Veng Yuen;Lambros S. Katafygiotis

  • Optimal Sensor Placement Methodology for Identification with Unmeasured Excitation

    Ka-Veng Yuen;Lambros S. Katafygiotis;Costas Papadimitriou;Neil Colin Mickleborough

Frequent Co-Authors

Lambros S. Katafygiotis
Lambros S. Katafygiotis Hong Kong University of Science and Technology
James L. Beck
James L. Beck California Institute of Technology
Wan-Huan Zhou
Wan-Huan Zhou University of Macau
Heung-Fai Lam
Heung-Fai Lam City University of Hong Kong
Siu-Kui Au
Siu-Kui Au Nanyang Technological University
Henry Leung
Henry Leung University of Calgary
Ana Isabel Miranda
Ana Isabel Miranda University of Aveiro
Costas Papadimitriou
Costas Papadimitriou University Of Thessaly
Behzad Fatahi
Behzad Fatahi University of Technology Sydney
Mark Girolami
Mark Girolami University of Cambridge

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Best Scientists Citing Ka-Veng Yuen

Trending Scientists

Recently Published Articles