Chao Hu

8.6k citations
183 papers · 6.8k indexed · 5 hit papers · h-index 41

Impact in

Papers in

Chao Hu

174 papers receiving 6.6k citations

Hit Papers

Uncertainty quantification in machine learning for engineering design and health prognostics: A tutorial 2023 · 103 citations
1032011202620162021100200300400

Peers

Chao Hu
Comparison fields: 5 of 152
  • Automotive Engineering 2.6k
  • Safety, Risk, Reliability and Quality 1.1k
  • Statistics, Probability and Uncertainty 824
  • Control and Systems Engineering 2.1k
  • Electrical and Electronic Engineering 2.7k
Replace Qiang Miao with:
Qiang Miao China
Noureddine Zerhouni France
Pingfeng Wang United States
Byeng D. Youn South Korea
Jianbo Yu China
Bin Zhang China
Jun Ni United States
Qiang Feng China
Nam Ho Kim United States
Hao Luo China
Chao Hu relative to Qiang Miao China Qiang Miao's profile →
Citations per field
00.5×3.4×
Qiang Miao · 1×
Citations per year

Countries citing papers authored by Chao Hu

Since Specialization
Citations

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

Fields of papers citing papers by Chao Hu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Chao Hu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Chao Hu Line = papers co-authored together Chao Hu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20250
3 20248
4 202437
5 202428
6 202411
7 20242
8 20240
9 202350
10 20235
11 202310
12 202297
13
A physics-informed deep learning approach for bearing fault detection
Hit paper breakdown →
2021184
14 20181
15 2015150
16 201441
17 201313
18 20124
19 20113
20 20115

About Chao Hu

Chao Hu is a scholar working on Statistics, Probability and Uncertainty, Automotive Engineering, Safety, Risk, Reliability and Quality, Control and Systems Engineering and Civil and Structural Engineering, having authored 183 papers that have together received 6.8k indexed citations. Recurring topics across this work include Advanced Battery Technologies Research (48 papers), Probabilistic and Robust Engineering Design (33 papers), Reliability and Maintenance Optimization (29 papers), Machine Fault Diagnosis Techniques (29 papers), Fault Detection and Control Systems (28 papers), Advancements in Battery Materials (25 papers), Structural Health Monitoring Techniques (21 papers) and Advanced Multi-Objective Optimization Algorithms (15 papers). The work is most often cited by research in Automotive Engineering (2.6k citations), Safety, Risk, Reliability and Quality (1.1k citations), Statistics, Probability and Uncertainty (824 citations), Control and Systems Engineering (2.1k citations) and Electrical and Electronic Engineering (2.7k citations). Chao Hu has collaborated with scholars based in United States, China and South Korea. Frequent co-authors include Byeng D. Youn, Pingfeng Wang, Mohammadkazem Sadoughi, Sheng Shen, Jaesik Chung, Gaurav Jain, Simon Laflamme, Adam Thelen, Zhixiong Li and Craig Schmidt. Their work appears in journals such as Structural and Multidisciplinary Optimization, Mechanical Systems and Signal Processing, Journal of Mechanical Design, Reliability Engineering & System Safety and Journal of Power Sources.

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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