Manuel Arias Chao

957 citations
17 papers · 584 indexed · 2 hit papers · h-index 8

Manuel Arias Chao

14 papers receiving 559 citations

Hit Papers

Fusing physics-based and deep learning models for prognos...246202120262022202450100150200

Peers

Manuel Arias Chao
Comparison fields: 5 of 67
  • Control and Systems Engineering 362
  • Safety, Risk, Reliability and Quality 136
  • Medical Laboratory Technology 19
  • Statistics, Probability and Uncertainty 47
  • Automotive Engineering 61
Replace Shaopeng Dong with:
Shaopeng Dong China
Song Fu China
André Listou Ellefsen Norway
Junqiang Liu China
Chengying Zhao China
Stefan Byttner Sweden
Tarek Berghout Algeria
Cunsong Wang China
Manuel Arias Chao relative to Shaopeng Dong China Shaopeng Dong's profile →
Citations per field
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Shaopeng Dong · 1×
Citations per year

Countries citing papers authored by Manuel Arias Chao

Since Specialization
Citations

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

Fields of papers citing papers by Manuel Arias Chao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 17 scholars most cited alongside Manuel Arias Chao, 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 Manuel Arias Chao Line = papers co-authored together Manuel Arias Chao links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1 20250
2 202414
3 20240
4 20241
5 202411
6 20231
7 20233
8
Fusing physics-based and deep learning models for prognosticsbreakdown →
2022246
9 202130
10 202119
11
Aircraft Engine Run-to-Failure Dataset under Real Flight Conditions for Prognostics and Diagnosticsbreakdown →
2021194
12 202141
13
Battery Model Calibration with Deep Reinforcement Learning
20200
14 20194
15 201913
16 20183
17 20154

About Manuel Arias Chao

Manuel Arias Chao is a scholar working on Control and Systems Engineering, Automotive Engineering and Fluid Flow and Transfer Processes, having authored 17 papers that have together received 584 indexed citations. Recurring topics across this work include Fault Detection and Control Systems (8 papers), Machine Fault Diagnosis Techniques (6 papers), Advanced Battery Technologies Research (4 papers), Anomaly Detection Techniques and Applications (3 papers), Electric Vehicles and Infrastructure (2 papers), Advanced Combustion Engine Technologies (2 papers), Reliability and Maintenance Optimization (2 papers) and Advanced Control Systems Optimization (1 paper). The work is most often cited by research in Control and Systems Engineering (362 citations), Safety, Risk, Reliability and Quality (136 citations) and Medical Laboratory Technology (19 citations). Manuel Arias Chao has collaborated with scholars based in Switzerland, United States and Sweden. Frequent co-authors include Olga Fink, Chetan S. Kulkarni, Kai Goebel, Yuan Tian, Luca Biggio, Xavier Olivé, Luis Basora, Márcia L. Baptista, Peter Mathé and Thomas Palmé. Their work appears in journals such as IEEE Access, Mechanical Systems and Signal Processing and Reliability Engineering & System Safety.

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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