Rih‐Teng Wu

1.1k total citations
22 papers, 821 citations indexed

About

Rih‐Teng Wu is a scholar working on Civil and Structural Engineering, Mechanical Engineering and Industrial and Manufacturing Engineering. According to data from OpenAlex, Rih‐Teng Wu has authored 22 papers receiving a total of 821 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Civil and Structural Engineering, 7 papers in Mechanical Engineering and 5 papers in Industrial and Manufacturing Engineering. Recurrent topics in Rih‐Teng Wu's work include Infrastructure Maintenance and Monitoring (11 papers), Structural Health Monitoring Techniques (9 papers) and Non-Destructive Testing Techniques (7 papers). Rih‐Teng Wu is often cited by papers focused on Infrastructure Maintenance and Monitoring (11 papers), Structural Health Monitoring Techniques (9 papers) and Non-Destructive Testing Techniques (7 papers). Rih‐Teng Wu collaborates with scholars based in Taiwan, United States and India. Rih‐Teng Wu's co-authors include Mohammad R. Jahanshahi, Fu‐Chen Chen, Tarutal Ghosh Mondal, Zheng Yi Wu, Ting‐Wei Liu, Fabio Semperlotti, Elisa Bertino, Dinesh Verma, Ankush Singla and Kuo‐Chun Chang and has published in prestigious journals such as Mechanical Systems and Signal Processing, Automation in Construction and Materials.

In The Last Decade

Rih‐Teng Wu

19 papers receiving 795 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Rih‐Teng Wu Taiwan 11 553 160 96 87 78 22 821
Ji Dang Japan 18 583 1.1× 124 0.8× 55 0.6× 40 0.5× 78 1.0× 65 755
Yousok Kim South Korea 21 966 1.7× 139 0.9× 45 0.5× 63 0.7× 94 1.2× 57 1.3k
Sandeep Sony Canada 7 699 1.3× 164 1.0× 53 0.6× 50 0.6× 176 2.3× 9 910
Carlos A. Perez-Ramirez Mexico 15 512 0.9× 186 1.2× 72 0.8× 45 0.5× 115 1.5× 35 953
Aurelio Domínguez-González Mexico 16 492 0.9× 250 1.6× 40 0.4× 88 1.0× 138 1.8× 51 888
Futao Ni China 7 513 0.9× 157 1.0× 65 0.7× 21 0.2× 48 0.6× 9 654
Steffen Freitag Germany 17 558 1.0× 108 0.7× 59 0.6× 40 0.5× 160 2.1× 64 824
Jingzhou Xin China 16 466 0.8× 120 0.8× 46 0.5× 22 0.3× 92 1.2× 50 708
Ge Ou United States 15 327 0.6× 267 1.7× 38 0.4× 77 0.9× 28 0.4× 47 733

Countries citing papers authored by Rih‐Teng Wu

Since Specialization
Citations

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

Fields of papers citing papers by Rih‐Teng Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rih‐Teng Wu. 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 Rih‐Teng Wu. The network helps show where Rih‐Teng Wu may publish in the future.

Co-authorship network of co-authors of Rih‐Teng Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Rih‐Teng Wu. A scholar is included among the top collaborators of Rih‐Teng Wu 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 Rih‐Teng Wu. Rih‐Teng Wu 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.
Wu, Rih‐Teng, et al.. (2025). Physics-guided GAN-based prognostic framework for seismic hysteresis loop and damage pattern in RC bridge columns. Engineering Structures. 328. 119668–119668.
2.
Wu, Rih‐Teng, et al.. (2025). Robotic inspection for autonomous crack segmentation and exploration using deep reinforcement learning. Automation in Construction. 176. 106009–106009. 1 indexed citations
3.
Wang, Ping‐Hsiung, Tzu‐Kang Lin, Patrick Huang, Rih‐Teng Wu, & Hsiao‐Hui Hung. (2025). Damage-based seismic performance design of reinforced concrete bridges using capacity-based inelastic displacement dual spectra. Soil Dynamics and Earthquake Engineering. 197. 109529–109529.
4.
Wang, Haiwei & Rih‐Teng Wu. (2025). A novel multi-scale feature fusion network for tile spalling segmentation in building exterior. Journal of Building Engineering. 112. 113589–113589.
5.
Chen, Yi‐Chang, et al.. (2024). Multi-task deep learning for crack segmentation and quantification in RC structures. Automation in Construction. 166. 105599–105599. 10 indexed citations
6.
Lin, Tzu‐Kang, et al.. (2024). Damage Scenario Prediction for Concrete Bridge Columns Using Deep Generative Networks. Structural Control and Health Monitoring. 2024(1). 1 indexed citations
7.
Wang, Haiwei & Rih‐Teng Wu. (2024). Unsupervised anomaly detection for tile spalling segmentation using synthetic outlier exposure and contrastive learning. Automation in Construction. 170. 105941–105941. 1 indexed citations
8.
Wu, Rih‐Teng, et al.. (2023). Development of a high-fidelity failure prediction system for reinforced concrete bridge columns using generative adversarial networks. Engineering Structures. 286. 116130–116130. 8 indexed citations
9.
Liu, Ting‐Wei, et al.. (2023). Deep-Learning-Based Acoustic Metamaterial Design for Attenuating Structure-Borne Noise in Auditory Frequency Bands. Materials. 16(5). 1879–1879. 25 indexed citations
10.
11.
Wu, Rih‐Teng, Ting‐Wei Liu, Mohammad R. Jahanshahi, & Fabio Semperlotti. (2021). Design of one-dimensional acoustic metamaterials using machine learning and cell concatenation. Structural and Multidisciplinary Optimization. 63(5). 2399–2423. 53 indexed citations
12.
Wu, Rih‐Teng, et al.. (2021). A physics-constrained deep learning based approach for acoustic inverse scattering problems. Mechanical Systems and Signal Processing. 164. 108190–108190. 19 indexed citations
13.
Wu, Rih‐Teng, et al.. (2020). Peak ground acceleration estimation using P-wave parameters and horizontal-to-vertical spectral ratios. Terrestrial Atmospheric and Oceanic Sciences. 31(1). 1–8. 18 indexed citations
14.
Mondal, Tarutal Ghosh, Mohammad R. Jahanshahi, Rih‐Teng Wu, & Zheng Yi Wu. (2020). Deep learning‐based multi‐class damage detection for autonomous post‐disaster reconnaissance. Structural Control and Health Monitoring. 27(4). 113 indexed citations
15.
Wu, Rih‐Teng, Ankush Singla, Mohammad R. Jahanshahi, & Elisa Bertino. (2019). Pruning Deep Neural Networks for Efficient Edge Computing in Internet of Things: A Structural Health Monitoring Case Study. 1 indexed citations
16.
Wu, Rih‐Teng & Mohammad R. Jahanshahi. (2018). Data fusion approaches for structural health monitoring and system identification: Past, present, and future. Structural Health Monitoring. 19(2). 552–586. 167 indexed citations
17.
Wu, Rih‐Teng & Mohammad R. Jahanshahi. (2018). Deep Convolutional Neural Network for Structural Dynamic Response Estimation and System Identification. Journal of Engineering Mechanics. 145(1). 176 indexed citations
18.
19.
Hsu, Ting‐Yu, Rih‐Teng Wu, & Kuo‐Chun Chang. (2016). Two Novel Approaches to Reduce False Alarm Due to Non‐Earthquake Events for On‐Site Earthquake Early Warning System. Computer-Aided Civil and Infrastructure Engineering. 31(7). 535–549. 14 indexed citations
20.
Lin, Tzu‐Kang, et al.. (2013). Evaluation of bridge instability caused by dynamic scour based on fractal theory. Smart Materials and Structures. 22(7). 75003–75003. 9 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Ji Dang Breakdown of academic impact, for papers by Yousok Kim Breakdown of academic impact, for papers by Sandeep Sony Breakdown of academic impact, for papers by Carlos A. Perez-Ramirez Breakdown of academic impact, for papers by Aurelio Domínguez-González Breakdown of academic impact, for papers by Futao Ni Breakdown of academic impact, for papers by Steffen Freitag Breakdown of academic impact, for papers by Jingzhou Xin Breakdown of academic impact, for papers by Ge Ou
Rankless by CCL
2026