Valeriia Cherepanova

About

Valeriia Cherepanova is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Epidemiology. According to data from OpenAlex, Valeriia Cherepanova has authored 10 papers receiving a total of 177 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Artificial Intelligence, 3 papers in Computer Vision and Pattern Recognition and 2 papers in Epidemiology. Recurrent topics in Valeriia Cherepanova’s work include Adversarial Robustness in Machine Learning (2 papers), Cardiac Imaging and Diagnostics (1 paper) and Neutropenia and Cancer Infections (1 paper). Valeriia Cherepanova is often cited by papers focused on Adversarial Robustness in Machine Learning (2 papers), Cardiac Imaging and Diagnostics (1 paper) and Neutropenia and Cancer Infections (1 paper). Valeriia Cherepanova collaborates with scholars based in United States, Ukraine and Russia. Valeriia Cherepanova's co-authors include Micah Goldblum, Tom Goldstein, Liam Fowl, Amin Ghiasi, Arjun K. Gupta, John P. Dickerson, Jonas Geiping, Theresa Smit, Jobie Budd and Maryam Shahmanesh and has published in prestigious journals such as Nature Medicine, British Journal of Cancer and Terapevticheskii arkhiv.

In The Last Decade

Co-authorship network of co-authors of Valeriia Cherepanova i

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Fields of papers citing papers by Valeriia Cherepanova

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Valeriia Cherepanova

Since Specialization

Citations

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