Gabriel Michau

788 total citations
21 papers, 511 citations indexed

About

Gabriel Michau is a scholar working on Control and Systems Engineering, Artificial Intelligence and Transportation. According to data from OpenAlex, Gabriel Michau has authored 21 papers receiving a total of 511 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Control and Systems Engineering, 8 papers in Artificial Intelligence and 6 papers in Transportation. Recurrent topics in Gabriel Michau's work include Machine Fault Diagnosis Techniques (7 papers), Human Mobility and Location-Based Analysis (6 papers) and Transportation Planning and Optimization (5 papers). Gabriel Michau is often cited by papers focused on Machine Fault Diagnosis Techniques (7 papers), Human Mobility and Location-Based Analysis (6 papers) and Transportation Planning and Optimization (5 papers). Gabriel Michau collaborates with scholars based in Switzerland, France and Australia. Gabriel Michau's co-authors include Olga Fink, Qin Wang, Thomas Palmé, Alfredo Nantes, Edward Chung, Yang Hu, Patrice Abry, Pierre Borgnat, Ashish Bhaskar and Nelly Pustelnik and has published in prestigious journals such as Proceedings of the National Academy of Sciences, IEEE Transactions on Industrial Electronics and Sensors.

In The Last Decade

Gabriel Michau

21 papers receiving 490 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gabriel Michau Switzerland 11 292 161 136 56 54 21 511
Hengchang Liu China 10 282 1.0× 59 0.4× 204 1.5× 92 1.6× 50 0.9× 26 559
Xuejin Gao China 13 365 1.3× 92 0.6× 199 1.5× 59 1.1× 20 0.4× 76 503
Wentian Zhao China 10 144 0.5× 130 0.8× 67 0.5× 18 0.3× 14 0.3× 19 573
Peng Dai China 10 104 0.4× 70 0.4× 171 1.3× 31 0.6× 141 2.6× 22 528
Pengcheng Jiang China 8 344 1.2× 41 0.3× 209 1.5× 107 1.9× 33 0.6× 26 460
Xili Wan China 12 58 0.2× 66 0.4× 51 0.4× 35 0.6× 41 0.8× 38 660
Zhenpeng Lao China 10 280 1.0× 75 0.5× 167 1.2× 88 1.6× 37 0.7× 25 422
Xinxin Yan China 11 83 0.3× 31 0.2× 92 0.7× 41 0.7× 39 0.7× 19 374
Xianghong Tang China 10 241 0.8× 134 0.8× 135 1.0× 77 1.4× 16 0.3× 31 424
Chenyu Liu China 11 368 1.3× 107 0.7× 242 1.8× 108 1.9× 42 0.8× 32 547

Countries citing papers authored by Gabriel Michau

Since Specialization
Citations

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

Fields of papers citing papers by Gabriel Michau

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gabriel Michau

This figure shows the co-authorship network connecting the top 25 collaborators of Gabriel Michau. A scholar is included among the top collaborators of Gabriel Michau 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 Gabriel Michau. Gabriel Michau 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.
Michau, Gabriel, et al.. (2024). Learning Informative Health Indicators Through Unsupervised Contrastive Learning. IEEE Transactions on Reliability. 74(1). 2408–2420. 4 indexed citations
2.
Michau, Gabriel, et al.. (2022). Controlled generation of unseen faults for Partial and Open-Partial domain adaptation. Reliability Engineering & System Safety. 230. 108857–108857. 34 indexed citations
3.
Michau, Gabriel, et al.. (2022). Fully learnable deep wavelet transform for unsupervised monitoring of high-frequency time series. Proceedings of the National Academy of Sciences. 119(8). 60 indexed citations
4.
Michau, Gabriel, et al.. (2022). Contrastive Feature Learning for Fault Detection and Diagnostics in Railway Applications. SSRN Electronic Journal. 4 indexed citations
5.
Michau, Gabriel & Olga Fink. (2021). Unsupervised transfer learning for anomaly detection: Application to complementary operating condition transfer. Knowledge-Based Systems. 216. 106816–106816. 92 indexed citations
6.
Michau, Gabriel, et al.. (2021). Domain Adaptations for Guided Wave SHM of Composites: Towards Fleet Monitoring. PHM Society European Conference. 6(1). 9–9. 6 indexed citations
7.
Michau, Gabriel, et al.. (2021). Interpretable Detection of Partial Discharge in Power Lines with Deep Learning. Repository for Publications and Research Data (ETH Zurich). 1 indexed citations
8.
Wang, Qin, Gabriel Michau, & Olga Fink. (2020). Missing-Class-Robust Domain Adaptation by Unilateral Alignment. IEEE Transactions on Industrial Electronics. 68(1). 663–671. 55 indexed citations
9.
Michau, Gabriel & Olga Fink. (2019). Fully Unsupervised Feature Alignment for Critical System Health Monitoring with Varied Operating Conditions. arXiv (Cornell University). 1 indexed citations
10.
Wang, Qin, Gabriel Michau, & Olga Fink. (2019). Domain Adaptive Transfer Learning for Fault Diagnosis. 279–285. 101 indexed citations
11.
Michau, Gabriel, Yang Hu, Thomas Palmé, & Olga Fink. (2019). Feature learning for fault detection in high-dimensional condition monitoring signals. Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability. 234(1). 104–115. 36 indexed citations
12.
Michau, Gabriel, Manuel Arias Chao, & Olga Fink. (2018). Feature Selecting Hierarchical Neural Network for Industrial System Health Monitoring. Annual Conference of the PHM Society. 10(1). 3 indexed citations
13.
Michau, Gabriel, Thomas Palmé, & Olga Fink. (2018). Fleet PHM for Critical Systems: Bi-level Deep Learning Approach for Fault Detection. Repository for Publications and Research Data (ETH Zurich). 13 indexed citations
14.
Michau, Gabriel, et al.. (2017). Deep Feature Learning Network for Fault Detection and Isolation. Annual Conference of the PHM Society. 9(1). 13 indexed citations
15.
Michau, Gabriel, Alfredo Nantes, Ashish Bhaskar, & Edward Chung. (2017). Bluetooth data in urban context: Retrieving vehicle trajectories. 1 indexed citations
16.
Michau, Gabriel, Alfredo Nantes, Ashish Bhaskar, et al.. (2017). Bluetooth Data in an Urban Context: Retrieving Vehicle Trajectories. IEEE Transactions on Intelligent Transportation Systems. 18(9). 2377–2386. 35 indexed citations
17.
Michau, Gabriel, Nelly Pustelnik, Pierre Borgnat, et al.. (2016). A Primal-Dual Algorithm for Link Dependent Origin Destination Matrix Estimation. IEEE Transactions on Signal and Information Processing over Networks. 3(1). 104–113. 15 indexed citations
18.
Michau, Gabriel, Alfredo Nantes, Edward Chung, Patrice Abry, & Pierre Borgnat. (2014). Retrieving Dynamic Origin-Destination Matrices from Bluetooth Data. QUT ePrints (Queensland University of Technology). 6 indexed citations
19.
Michau, Gabriel, Alfredo Nantes, Edward Chung, Patrice Abry, & Pierre Borgnat. (2014). Retrieving trip information from a discrete detectors network : The case of Brisbane Bluetooth detectors. QUT ePrints (Queensland University of Technology). 1 indexed citations
20.
Michau, Gabriel, Alfredo Nantes, & Edward Chung. (2013). Towards the retrieval of accurate OD matrices from bluetooth data: Lessons learned from 2 years of data. QUT ePrints (Queensland University of Technology). 4 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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