Paul Boniol

815 total citations
24 papers, 535 citations indexed

About

Paul Boniol is a scholar working on Signal Processing, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Paul Boniol has authored 24 papers receiving a total of 535 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Signal Processing, 22 papers in Artificial Intelligence and 9 papers in Computer Networks and Communications. Recurrent topics in Paul Boniol's work include Time Series Analysis and Forecasting (23 papers), Anomaly Detection Techniques and Applications (20 papers) and Network Security and Intrusion Detection (9 papers). Paul Boniol is often cited by papers focused on Time Series Analysis and Forecasting (23 papers), Anomaly Detection Techniques and Applications (20 papers) and Network Security and Intrusion Detection (9 papers). Paul Boniol collaborates with scholars based in France, United States and Greece. Paul Boniol's co-authors include Themis Palpanas, John Paparrizos, Michael J. Franklin, Ruey S. Tsay, Michele Linardi, Mohammed Meftah, Aaron J. Elmore, Panos Trahanias, Qinghua Liu and Michalis Vazirgiannis and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Knowledge and Data Engineering and Proceedings of the VLDB Endowment.

In The Last Decade

Paul Boniol

23 papers receiving 528 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Paul Boniol France	12	459	414	200	41	37	24	535
Dragomir Yankov United States	10	235 0.5×	231 0.6×	62 0.3×	59 1.4×	14 0.4×	27	398
Yunyue Zhu United States	10	259 0.6×	396 1.0×	127 0.6×	31 0.8×	23 0.6×	16	580
Kostas Tsichlas Greece	9	255 0.6×	109 0.3×	191 1.0×	3 0.1×	15 0.4×	48	386
Yongqian Sun China	12	345 0.8×	119 0.3×	491 2.5×	5 0.1×	30 0.8×	49	592
Yixin Chen United States	8	134 0.3×	75 0.2×	161 0.8×	10 0.2×	19 0.5×	14	262
Kostas Zoumpatianos France	14	237 0.5×	467 1.1×	174 0.9×	29 0.7×	4 0.1×	21	589
Dapeng Liu China	6	245 0.5×	103 0.2×	220 1.1×	2 0.0×	19 0.5×	16	339
Bowei Xi United States	10	186 0.4×	100 0.2×	118 0.6×	3 0.1×	22 0.6×	20	285
Rudolf B. Blažek United States	5	146 0.3×	42 0.1×	130 0.7×	5 0.1×	82 2.2×	8	351
Luis Muñoz-González United Kingdom	8	353 0.8×	90 0.2×	113 0.6×	6 0.1×	34 0.9×	14	438

Countries citing papers authored by Paul Boniol

Since Specialization

Citations

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

Fields of papers citing papers by Paul Boniol

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Paul Boniol

This figure shows the co-authorship network connecting the top 25 collaborators of Paul Boniol. A scholar is included among the top collaborators of Paul Boniol 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 Paul Boniol. Paul Boniol is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Paparrizos, John, et al.. (2025). Advances in Time-Series Anomaly Detection: Algorithms, Benchmarks, and Evaluation Measures. SPIRE - Sciences Po Institutional REpository. 6151–6161. 5 indexed citations

Boniol, Paul, et al.. (2025). $k$-Graph: A Graph Embedding for Interpretable Time Series Clustering. IEEE Transactions on Knowledge and Data Engineering. 37(5). 2680–2694. 1 indexed citations

Boniol, Paul, A. Krishna, Qinghua Liu, et al.. (2025). VUS: effective and efficient accuracy measures for time-series anomaly detection. The VLDB Journal. 34(3). 10 indexed citations

Truong, Charles, et al.. (2025). Time Series Motif Discovery: A Comprehensive Evaluation. Proceedings of the VLDB Endowment. 18(7). 2226–2239.

Boniol, Paul, Danping Wang, Laurent Oudre, et al.. (2024). Arm-CODA: A Data Set of Upper-limb Human Movement During Routine Examination. Image Processing On Line. 14. 1–13. 4 indexed citations

Boniol, Paul, John Paparrizos, & Themis Palpanas. (2024). An Interactive Dive into Time-Series Anomaly Detection. 5382–5386. 7 indexed citations

Liu, Qinghua, Paul Boniol, Themis Palpanas, & John Paparrizos. (2024). Time-Series Anomaly Detection: Overview and New Trends. Proceedings of the VLDB Endowment. 17(12). 4229–4232. 13 indexed citations

Boniol, Paul, et al.. (2024). ADecimo: Model Selection for Time Series Anomaly Detection. 5441–5444. 6 indexed citations

Boniol, Paul, Qinghua Liu, Mong‐Han Huang, Themis Palpanas, & John Paparrizos. (2024). Dive into Time-Series Anomaly Detection: A Decade Review. arXiv (Cornell University). 1 indexed citations

10.

Boniol, Paul, et al.. (2023). dCNN/dCAM: anomaly precursors discovery in multivariate time series with deep convolutional neural networks. SHILAP Revista de lepidopterología. 4. 2 indexed citations

11.

Boniol, Paul, John Paparrizos, Themis Palpanas, et al.. (2022). Theseus. Proceedings of the VLDB Endowment. 15(12). 3702–3705. 15 indexed citations

12.

Paparrizos, John, Paul Boniol, Themis Palpanas, et al.. (2022). Volume under the surface. Proceedings of the VLDB Endowment. 15(11). 2774–2787. 68 indexed citations

13.

Boniol, Paul, et al.. (2022). dCAM: Dimension-wise Class Activation Map for Explaining Multivariate Data Series Classification. Proceedings of the 2022 International Conference on Management of Data. 1175–1189. 11 indexed citations

14.

Boniol, Paul, et al.. (2021). Unsupervised and scalable subsequence anomaly detection in large data series. The VLDB Journal. 30(6). 909–931. 43 indexed citations

15.

Boniol, Paul, John Paparrizos, Themis Palpanas, & Michael J. Franklin. (2021). SAND. Proceedings of the VLDB Endowment. 14(10). 1717–1729. 70 indexed citations

16.

Boniol, Paul, et al.. (2021). Correction to: Unsupervised and scalable subsequence anomaly detection in large data series. The VLDB Journal. 32(2). 469–469. 1 indexed citations

17.

Boniol, Paul, et al.. (2020). PERFORMANCE IN THE COURTROOM: AUTOMATED PROCESSING AND VISUALIZATION OF APPEAL COURT DECISIONS IN FRANCE. Knowledge Discovery and Data Mining. 15(2). 11–17. 4 indexed citations

18.

Boniol, Paul, et al.. (2020). GraphAn. Proceedings of the VLDB Endowment. 13(12). 2941–2944. 27 indexed citations

19.

Boniol, Paul, et al.. (2020). SAD: An Unsupervised System for Subsequence Anomaly Detection. 1778–1781. 14 indexed citations

20.

Boniol, Paul & Themis Palpanas. (2020). Series2Graph. Proceedings of the VLDB Endowment. 13(12). 1821–1834. 67 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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