Liudmila Ulanova

15 total papers · 1.2k total citations
11 papers, 751 citations indexed

About

Liudmila Ulanova is a scholar working on Signal Processing, Artificial Intelligence and Economics and Econometrics. According to data from OpenAlex, Liudmila Ulanova has authored 11 papers receiving a total of 751 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Signal Processing, 7 papers in Artificial Intelligence and 2 papers in Economics and Econometrics. Recurrent topics in Liudmila Ulanova's work include Time Series Analysis and Forecasting (9 papers), Anomaly Detection Techniques and Applications (7 papers) and Music and Audio Processing (3 papers). Liudmila Ulanova is often cited by papers focused on Time Series Analysis and Forecasting (9 papers), Anomaly Detection Techniques and Applications (7 papers) and Music and Audio Processing (3 papers). Liudmila Ulanova collaborates with scholars based in United States, Brazil and Austria. Liudmila Ulanova's co-authors include Eamonn Keogh, Nurjahan Begum, Yifei Ding, Chin‐Chia Michael Yeh, Hoang Anh Dau, Yan Zhu, Diego Furtado Silva, Abdullah Mueen, Jun Wang and Pamela Bhattacharya and has published in prestigious journals such as Sensors, Data Mining and Knowledge Discovery and Journal of Computer Science.

In The Last Decade

Liudmila Ulanova

11 papers receiving 730 citations

Hit Papers

Matrix Profile I: All Pai... 2016 2026 2019 2022 2016 100 200 300

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Liudmila Ulanova 485 408 116 105 101 11 751
S. Chu 427 0.9× 307 0.8× 82 0.7× 114 1.1× 99 1.0× 7 739
Usue Mori 332 0.7× 361 0.9× 87 0.8× 49 0.5× 158 1.6× 23 792
Alain Ketterlin 346 0.7× 229 0.6× 90 0.8× 103 1.0× 47 0.5× 13 761
Iqbal Jamal 265 0.5× 361 0.9× 74 0.6× 79 0.8× 85 0.8× 11 665
Quang Do 195 0.4× 389 1.0× 27 0.2× 85 0.8× 183 1.8× 29 798
Mustafa Gökçe Baydoğan 470 1.0× 451 1.1× 114 1.0× 52 0.5× 28 0.3× 29 694
Nurjahan Begum 454 0.9× 396 1.0× 119 1.0× 79 0.8× 69 0.7× 8 628
Hoang Anh Dau 480 1.0× 430 1.1× 113 1.0× 98 0.9× 76 0.8× 12 711
Zhengzheng Xing 393 0.8× 403 1.0× 90 0.8× 62 0.6× 48 0.5× 8 669
Ying Zhang 123 0.3× 465 1.1× 20 0.2× 156 1.5× 89 0.9× 33 778

Countries citing papers authored by Liudmila Ulanova

Since Specialization
Citations

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

Fields of papers citing papers by Liudmila Ulanova

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Liudmila Ulanova

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

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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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