Charles Truong

1.4k total citations · 1 hit paper
25 papers, 771 citations indexed

About

Charles Truong is a scholar working on Signal Processing, Artificial Intelligence and Biomedical Engineering. According to data from OpenAlex, Charles Truong has authored 25 papers receiving a total of 771 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Signal Processing, 7 papers in Artificial Intelligence and 7 papers in Biomedical Engineering. Recurrent topics in Charles Truong's work include Time Series Analysis and Forecasting (7 papers), Balance, Gait, and Falls Prevention (4 papers) and Statistical Methods and Inference (4 papers). Charles Truong is often cited by papers focused on Time Series Analysis and Forecasting (7 papers), Balance, Gait, and Falls Prevention (4 papers) and Statistical Methods and Inference (4 papers). Charles Truong collaborates with scholars based in France, China and Nepal. Charles Truong's co-authors include Laurent Oudre, Nicolas Vayatis, Damien Ricard, Thomas Moreau, Pierre‐Paul Vidal, Stéphane Buffat, Rémi Barrois, Catherine de Waele, A. Yelnik and Sébastien Laporte and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and The Journal of Physiology.

In The Last Decade

Charles Truong

18 papers receiving 754 citations

Hit Papers

Selective review of offline change point detection methods 2019 2026 2021 2023 2019 200 400 600
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.

  1. Selective review of offline change point detection methods
    2019 618 citations Charles Truong, Laurent Oudre et al. Signal Processing profile →

Peers

Charles Truong
Samaneh Aminikhanghahi United States
Simone Vantini Italy
Thomas Burr United States
Ta‐Hsin Li United States
Kris De Brabanter United States
Mark Ebden United Kingdom
Tadayoshi Fushiki Japan
Valeria Vitelli Norway
Ian Nabney United Kingdom
Dost Muhammad Khan Pakistan
Samaneh Aminikhanghahi United States
Charles Truong
Citations per year, relative to Charles Truong Charles Truong (= 1×) peers Samaneh Aminikhanghahi

Countries citing papers authored by Charles Truong

Since Specialization
Citations

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

Fields of papers citing papers by Charles Truong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Charles Truong

This figure shows the co-authorship network connecting the top 25 collaborators of Charles Truong. A scholar is included among the top collaborators of Charles Truong 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 Charles Truong. Charles Truong 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.
Yu, Dan, et al.. (2025). Environmental Humanities South: Decolonizing Nature in Highland Asia. Challenges. 16(2). 19–19.
2.
Truong, Charles, et al.. (2025). Time Series Motif Discovery: A Comprehensive Evaluation. Proceedings of the VLDB Endowment. 18(7). 2226–2239.
3.
PETROV, K. A., Jacqueline Leroy, Véronique Bernard, et al.. (2024). An α7 nicotinic and GABAB receptor‐mediated pathway controls acetylcholine release in the tripartite neuromuscular junction. The Journal of Physiology. 603(2). 507–527.
4.
Truong, Charles, et al.. (2024). Persistence-Based Motif Discovery in Time Series. IEEE Transactions on Knowledge and Data Engineering. 36(11). 6814–6827. 2 indexed citations
5.
Truong, Charles, et al.. (2024). Symbolic Representation for Time Series. SPIRE - Sciences Po Institutional REpository. 1962–1966.
6.
Truong, Charles, et al.. (2024). Structured Loss for Deep Change-Point Detection. SPIRE - Sciences Po Institutional REpository. 1706–1710. 1 indexed citations
7.
Truong, Charles, et al.. (2024). Linear-trend normalization for multivariate subsequence similarity search. SPIRE - Sciences Po Institutional REpository. 167–175. 2 indexed citations
8.
Truong, Charles & Laurent Oudre. (2023). Supervised Change-Point Detection with Dimension Reduction. SPIRE - Sciences Po Institutional REpository. 1005–1009.
9.
l′Escalopier, Nicolas de, et al.. (2023). A Machine Learning Pipeline for Gait Analysis in a Semi Free-Living Environment. Sensors. 23(8). 4000–4000. 2 indexed citations
10.
Truong, Charles, et al.. (2023). Unsupervised classification of plethysmography signals with advanced visual representations. Frontiers in Physiology. 14. 1154328–1154328. 1 indexed citations
11.
Truong, Charles, et al.. (2023). A Data Set for Fall Detection with Smart Floor Sensors. Image Processing On Line. 13. 183–197. 2 indexed citations
12.
Truong, Charles, et al.. (2021). Bayesian Feature Discovery for Predictive Maintenance. 2021 29th European Signal Processing Conference (EUSIPCO). 1421–1425.
13.
Truong, Charles, Thomas Moreau, Pierre‐Paul Vidal, et al.. (2019). A Data Set for the Study of Human Locomotion with Inertial Measurements Units. Image Processing On Line. 9. 381–390. 14 indexed citations
14.
Truong, Charles, Laurent Oudre, & Nicolas Vayatis. (2019). Selective review of offline change point detection methods. Signal Processing. 167. 107299–107299. 618 indexed citations breakdown →
15.
Truong, Charles, Laurent Oudre, & Nicolas Vayatis. (2018). A review of change point detection methods.. arXiv (Cornell University). 32 indexed citations
16.
Oudre, Laurent, Thomas Moreau, Charles Truong, et al.. (2018). Template-Based Step Detection with Inertial Measurement Units. Sensors. 18(11). 4033–4033. 28 indexed citations
17.
Truong, Charles, et al.. (2017). Penalty learning for changepoint detection. 1569–1573. 10 indexed citations
18.
Barrois, Rémi, Laurent Oudre, Thomas Moreau, et al.. (2016). An Automated Recording Method in Clinical Consultation to Rate the Limp in Lower Limb Osteoarthritis. PLoS ONE. 11(10). e0164975–e0164975. 26 indexed citations
19.
Barrois, Rémi, Laurent Oudre, Thomas Moreau, et al.. (2015). Quantify osteoarthritis gait at the doctor’s office: a simple pelvis accelerometer based method independent from footwear and aging. Computer Methods in Biomechanics & Biomedical Engineering. 18(sup1). 1880–1881. 12 indexed citations
20.
Oudre, Laurent, Thomas Moreau, Charles Truong, et al.. (2015). Détection automatique des pas à partir de capteurs inertiels pour la quantification de la marche en consultation. Neurophysiologie Clinique. 45(4-5). 394–394. 5 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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