David He

7.0k total citations · 2 hit papers
162 papers, 5.5k citations indexed

About

David He is a scholar working on Control and Systems Engineering, Mechanical Engineering and Mechanics of Materials. According to data from OpenAlex, David He has authored 162 papers receiving a total of 5.5k indexed citations (citations by other indexed papers that have themselves been cited), including 96 papers in Control and Systems Engineering, 85 papers in Mechanical Engineering and 32 papers in Mechanics of Materials. Recurrent topics in David He's work include Machine Fault Diagnosis Techniques (85 papers), Gear and Bearing Dynamics Analysis (50 papers) and Fault Detection and Control Systems (40 papers). David He is often cited by papers focused on Machine Fault Diagnosis Techniques (85 papers), Gear and Bearing Dynamics Analysis (50 papers) and Fault Detection and Control Systems (40 papers). David He collaborates with scholars based in United States, China and Türkiye. David He's co-authors include Miao He, Ming Dong, Eric Bechhoefer, Yongzhi Qu, Xueyi Li, Jialin Li, Ruoyu Li, Jae Yoon, Junda Zhu and Brandon Van Hecke and has published in prestigious journals such as JAMA, SHILAP Revista de lepidopterología and Scientific Reports.

In The Last Decade

David He

153 papers receiving 5.3k citations

Hit Papers

align trajectories sort by overperformance

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.

Deep Learning Based Approach for Bearing Fault Diagnosis

2017 373 citations Miao He, David He profile →
Using Deep Learning-Based Approach to Predict Remaining Useful Life of Rotating Components

2017 370 citations David He et al. profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
David He	3.1k	2.3k	1.1k	719	640	162	5.5k
Kamal Medjaher	2.7k 0.9×	1.5k 0.6×	654 0.6×	916 1.3×	413 0.6×	123	4.1k
Bo‐Suk Yang	3.8k 1.3×	2.0k 0.9×	1.2k 1.1×	743 1.0×	428 0.7×	109	5.9k
Tao Yan	3.2k 1.1×	1.9k 0.8×	906 0.8×	1.2k 1.7×	285 0.4×	52	4.4k
Jing Lin	3.6k 1.2×	2.3k 1.0×	1.1k 1.0×	514 0.7×	233 0.4×	145	5.5k
Jianbo Yu	3.7k 1.2×	3.0k 1.3×	999 0.9×	606 0.8×	1.7k 2.6×	316	7.9k
Zhibin Zhao	4.0k 1.3×	2.2k 1.0×	1.1k 1.0×	349 0.5×	514 0.8×	148	6.3k
Chuang Sun	5.2k 1.7×	2.8k 1.2×	1.5k 1.4×	501 0.7×	784 1.2×	127	7.2k
Yimin Zhang	1.4k 0.5×	2.6k 1.1×	1.4k 1.3×	293 0.4×	275 0.4×	329	5.2k
Te Han	3.1k 1.0×	1.7k 0.7×	917 0.9×	201 0.3×	314 0.5×	90	4.4k
Abhinav Saxena	2.9k 1.0×	992 0.4×	887 0.8×	1.3k 1.8×	191 0.3×	116	5.1k

Countries citing papers authored by David He

Since Specialization

Citations

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

Fields of papers citing papers by David He

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David He

This figure shows the co-authorship network connecting the top 25 collaborators of David He. A scholar is included among the top collaborators of David He 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 David He. David He 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:

20 of 20 papers shown

Yang, Kai‐Cheng, Shengjie Luo, Jiacheng Sun, et al.. (2025). How Numerical Precision Affects Arithmetical Reasoning Capabilities of LLMs. 46–85.

Zhou, Yao, et al.. (2024). Overview and trend analysis of global hot spring research based on bibliometrics and knowledge graph visualization. Complementary Therapies in Medicine. 87. 103102–103102. 1 indexed citations

He, David, et al.. (2023). A Natural Language Processing Based Planetary Gearbox Fault Diagnosis with Acoustic Emission Signals. 323. 1–6. 3 indexed citations

Li, Jialin & David He. (2020). A Bayesian Optimization AdaBN-DCNN Method With Self-Optimized Structure and Hyperparameters for Domain Adaptation Remaining Useful Life Prediction. IEEE Access. 8. 41482–41501. 37 indexed citations

Li, Xueyi, Jialin Li, Chengying Zhao, Yongzhi Qu, & David He. (2020). Gear pitting fault diagnosis with mixed operating conditions based on adaptive 1D separable convolution with residual connection. Mechanical Systems and Signal Processing. 142. 106740–106740. 88 indexed citations

Li, Jialin, Xueyi Li, & David He. (2019). Domain Adaptation Remaining Useful Life Prediction Method Based on AdaBN-DCNN. 1–6. 15 indexed citations

He, David, et al.. (2019). Performance and load testing: Tools and challenges. 1(1). 57–62. 6 indexed citations

Li, Jialin, Xueyi Li, David He, & Yongzhi Qu. (2019). A domain adaptation model for early gear pitting fault diagnosis based on deep transfer learning network. Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability. 234(1). 168–182. 27 indexed citations

Li, Jialin, Xueyi Li, & David He. (2019). A Directed Acyclic Graph Network Combined With CNN and LSTM for Remaining Useful Life Prediction. IEEE Access. 7. 75464–75475. 187 indexed citations

10.

Li, Xueyi, Jialin Li, Yongzhi Qu, & David He. (2019). Gear Pitting Fault Diagnosis Using Integrated CNN and GRU Network with Both Vibration and Acoustic Emission Signals. Applied Sciences. 9(4). 768–768. 84 indexed citations

11.

Qu, Yongzhi, Yue Zhang, Miao He, et al.. (2019). Gear pitting fault diagnosis using disentangled features from unsupervised deep learning. Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability. 233(5). 719–730. 10 indexed citations

12.

Li, Jialin, Xueyi Li, David He, & Yongzhi Qu. (2019). A Novel Method for Early Gear Pitting Fault Diagnosis Using Stacked SAE and GBRBM. Sensors. 19(4). 758–758. 34 indexed citations

13.

Qu, Yongzhi, et al.. (2017). Detection of Pitting in Gears Using a Deep Sparse Autoencoder. Applied Sciences. 7(5). 515–515. 51 indexed citations

14.

Yoon, Jae, David He, & Brandon Van Hecke. (2014). A PHM Approach to Additive Manufacturing Equipment Health Monitoring, Fault Diagnosis, and Quality Control. Annual Conference of the PHM Society. 6(1). 33 indexed citations

15.

Zhu, Junda, Eric Bechhoefer, David He, & Yongzhi Qu. (2013). A New Acoustic Emission Sensor Based Gear Fault Detection Approach. SHILAP Revista de lepidopterología. 28 indexed citations

16.

Qu, Yongzhi, Junda Zhu, David He, Bin Qiu, & Eric Bechhoefer. (2013). Development of a new acoustic emission based fault diagnosis tool for gearbox. 1–9. 10 indexed citations

17.

Periyasamy, K., et al.. (2011). A REQUIREMENTS EDITOR FOR TEACHING REQUIREMENTS ENGINEERING. 4092–4100. 1 indexed citations

18.

He, David, et al.. (2010). Gear Fault Location Detection for Split Torque Gearbox using AE Sensors. Annual Conference of the PHM Society. 2(1). 7 indexed citations

19.

He, David, et al.. (2006). Joint statistical design of double sampling X and s charts. Quality Engineering. 51(4). 369–374. 1 indexed citations

20.

He, David, et al.. (2003). Solving the n -job 3-stage flexible flowshop scheduling problem using an agent-based approach. International Journal of Production Research. 42(4). 777–799. 29 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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