Haiyue Wu

510 total citations · 1 hit paper
10 papers, 310 citations indexed

About

Haiyue Wu is a scholar working on Control and Systems Engineering, Industrial and Manufacturing Engineering and Safety, Risk, Reliability and Quality. According to data from OpenAlex, Haiyue Wu has authored 10 papers receiving a total of 310 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Control and Systems Engineering, 4 papers in Industrial and Manufacturing Engineering and 2 papers in Safety, Risk, Reliability and Quality. Recurrent topics in Haiyue Wu's work include Machine Fault Diagnosis Techniques (5 papers), Fault Detection and Control Systems (3 papers) and Quality and Safety in Healthcare (2 papers). Haiyue Wu is often cited by papers focused on Machine Fault Diagnosis Techniques (5 papers), Fault Detection and Control Systems (3 papers) and Quality and Safety in Healthcare (2 papers). Haiyue Wu collaborates with scholars based in United States and China. Haiyue Wu's co-authors include John W. Sutherland, Wo Jae Lee, Matthew J. Triebe, Han‐Jun Kim, Martin Byung‐Guk Jun, Huitaek Yun, Aihua Huang, Zhenning Li, Shumin Feng and Xiaoyu Zhou and has published in prestigious journals such as The International Journal of Advanced Manufacturing Technology, Journal of Manufacturing Systems and Procedia Manufacturing.

In The Last Decade

Haiyue Wu

9 papers receiving 292 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.

A transformer-based approach for novel fault detection and fault classification/diagnosis in manufacturing: A rotary system application

2023 78 citations Haiyue Wu, Matthew J. Triebe et al. Journal of Manufacturing Systems profile →

Peers

Haiyue Wu

CSE

IME

ME

AI

MM

Wo Jae Lee United States

Jovani Dalzochio Brazil

Francesca Calabrese Italy

Marcel Kettelgerdes Germany

Pier Francesco Orrù Italy

Khaled Ziane Canada

Gaige Chen China

Zakwan Skaf United Kingdom

Andreas Kimmig Germany

Zoi Arkouli Greece

Wo Jae Lee United States

Haiyue Wu

144 ×1.0

CSE

166 ×1.8

IME

124 ×1.6

ME

62 ×1.3

AI

29 ×0.7

MM

Citations per year, relative to Haiyue Wu Haiyue Wu (= 1×) peers Wo Jae Lee

Countries citing papers authored by Haiyue Wu

Since Specialization

Citations

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

Fields of papers citing papers by Haiyue Wu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Haiyue Wu

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

All Works

Sort: Min cites: Since: Top N: Style:

10 of 10 papers shown

1.

Birge, John R., et al.. (2025). Cluster Aware Graph Anomaly Detection. 1771–1782.

2.

Triebe, Matthew J., et al.. (2023). Perspectives on future research directions in green manufacturing for discrete products. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 1(1). 10–10. 8 indexed citations

3.

Wu, Haiyue, Matthew J. Triebe, & John W. Sutherland. (2023). A transformer-based approach for novel fault detection and fault classification/diagnosis in manufacturing: A rotary system application. Journal of Manufacturing Systems. 67. 439–452. 78 indexed citations breakdown →

4.

Huang, Aihua, et al.. (2022). A review of research on smart manufacturing in support of environmental sustainability. 5(2/3/4). 132–163. 1 indexed citations

5.

Wu, Haiyue, Aihua Huang, & John W. Sutherland. (2022). Condition-Based Monitoring and Novel Fault Detection Based on Incremental Learning Applied to Rotary Systems. Procedia CIRP. 105. 788–793. 7 indexed citations

6.

Wu, Haiyue, Aihua Huang, & John W. Sutherland. (2021). Layer-wise relevance propagation for interpreting LSTM-RNN decisions in predictive maintenance. The International Journal of Advanced Manufacturing Technology. 118(3-4). 963–978. 22 indexed citations

7.

Wu, Haiyue, Aihua Huang, & John W. Sutherland. (2020). Avoiding Environmental Consequences of Equipment Failure via an LSTM-Based Model for Predictive Maintenance. Procedia Manufacturing. 43. 666–673. 26 indexed citations

8.

Lee, Wo Jae, Haiyue Wu, Huitaek Yun, et al.. (2019). Predictive Maintenance of Machine Tool Systems Using Artificial Intelligence Techniques Applied to Machine Condition Data. Procedia CIRP. 80. 506–511. 142 indexed citations

9.

Lee, Wo Jae, Haiyue Wu, Aihua Huang, & John W. Sutherland. (2019). Learning via acceleration spectrograms of a DC motor system with application to condition monitoring. The International Journal of Advanced Manufacturing Technology. 106(3-4). 803–816. 17 indexed citations

10.

Feng, Shumin, et al.. (2016). Factors of Perceived Waiting Time and Implications on Passengers’ Satisfaction with Waiting Time. PROMET - Traffic&Transportation. 28(2). 155–163. 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.

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