Liudmila Ulanova

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 7 papers receiving a total of 228 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Signal Processing, 4 papers in Artificial Intelligence and 2 papers in Economics and Econometrics. Recurrent topics in Liudmila Ulanova’s work include Time Series Analysis and Forecasting (5 papers), Anomaly Detection Techniques and Applications (4 papers) and Complex Systems and Time Series Analysis (2 papers). Liudmila Ulanova is often cited by papers focused on Time Series Analysis and Forecasting (5 papers), Anomaly Detection Techniques and Applications (4 papers) and Complex Systems and Time Series Analysis (2 papers). Liudmila Ulanova collaborates with scholars based in United States, Australia and Brazil. Liudmila Ulanova's co-authors include Eamonn Keogh, Nurjahan Begum, Chin‐Chia Michael Yeh, Yifei Ding, Iulian Neamtiu, Pamela Bhattacharya, Zachary Zimmerman, Yan Zhu, Diego Furtado Silva and Eamonn Keogh and has published in prestigious journals such as Sensors, Data Mining and Knowledge Discovery and Journal of Computer Science.

In The Last Decade

Co-authorship network of co-authors of Liudmila Ulanova i

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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.

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).

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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