Arévalo Barco, Irina

Quantitative Methods

PhD: Universidad Autónoma de Madrid

BIO

Irina Arévalo has a PhD in Mathematics from Universidad Autónoma de Madrid. She specialises in Complex Analysis and Operator Theory, and has taught graduate-level courses on Mathematical Analysis in Mathematics, Physics and Engineering degrees, and published more than ten papers on Complex Analysis, Applied Statistics, and Artificial Intelligence.

After her PhD, she worked as a Data Scientist, Artificial Intelligence Researcher, and Analytics Manager in different industries, including banking and tech.

Publications in Scientific Journals

Salmeron, Jose L.; Arévalo, Irina; Ruiz-Celma, Antonio: “Benchmarking federated strategies in Peerto-Peer Federated learning for biomedical data”, Heliyon 9(6), Art. e16925, 2023.

Salmeron, Jose L; Arévalo, Irina: “A privacy-preserving, distributed and cooperative FCM-based learning approach for cancer research”, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Rough Sets: International Joint Conference, IJCRS 2020, Havana, 12179 LNAI, 477-487, 2020.

Arévalo, Irina; Vukotic, Dragan: “Weighted composition operators in functional Banach spaces: an axiomatic approach”, Journal of Spectral Theory, 10(2), 673-701, 2020.

Arévalo, Irina; Contreras, Manuel D; Rodríguez-Piazza, Luis: “Semigroups of composition operators and integral operators on mixed norm spaces”, Revista Matemática Complutense 32(3), 767-798, 2019.

Arévalo, Irina: “A characterization of the inclusions between mixed norm spaces”, Journal of Mathematical Analysis and Applications, 429(2), 942-955, 2015.

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