Irina Arévalo holds a PhD in Mathematics from Universidad Autonoma de Madrid and a PhD in Artificial Intelligence from Universidad Pablo de Olavide, and is currently an Assistant Professor at Universidad Politecnica de Madrid. In her first PhD, she specialized in Complex Analysis and Operator Theory and has taught graduate-level courses in mathematical analysis in Mathematics, Physics and Engineering degrees. After her PhD she worked as a Data Scientist, Researcher in Artificial Intelligence, and Analytics Manager in several industries, such as banking and tech.

Her second PhD aligned with her current research interest, Distributed Machine Learning, especifically in Federated Learning. Her work has focused on new aggregations to build the federated global model, new encryption methods to ensure the security of the federated system, methodologies to federate Fuzzy Cognitive Maps, and explainability. Irina has published more than 10 papers in Complex Analysis, Applied Statistics, and Artificial Intelligence.

Positions held

Postdoctoral

• [September 2025-] Assistant Professor of Applied Mathematics at UPM, Madrid, Spain.


• [September 2023-August 2025] Assistant Professor of Computer Science and Artificial Intelligence at CUNEF University, Madrid, Spain.


• [July 2022-September 2023] Analytics Manager at Lookiero, Bilbao, Spain.


• [April 2020 - June 2022] AI Researcher and Senior Data Scientist at ING, Madrid, Spain.


• [July 2018 - April 2020] AI Researcher and Data Scientist at BBVA, Madrid, Spain.


• [February 2018 - July 2018] Senior Data Scientist Consultant at Kernel Analytics, Madrid, Spain.


• [July 2017 - February 2018] Data Scientist at Vueling, Barcelona, Spain.

Predoctoral

• [January 2014 - July 2017] Teaching Assistant at Universidad Autonoma de Madrid, Madrid, Spain.

Research

Research Interests

Distributed Artificial Intelligence, Federated Learning, eXplainable Artificial Intelligence, Bias and Fairness

Publications

Selected papers

• I. Arevalo and M. Oliva (2026). CAFP: A post-processing framework for group fairness via counterfactual model averaging. Knowledge-Based Systems Volume 342.


• J. L. Salmeron and I. Arevalo (2026). Spectral biclustering-driven scalability for post-hoc explainability in recommender systems. Knowledge-Based Systems Volume 342.


• I. Arevalo and J. L. Salmeron (2025). Model-agnostic post-hoc explainability for recommender systems. Expert Systems with Applications 129608.


• J. L. Salmeron and I. Arevalo (2024). Concurrent vertical and horizontal federated learning with fuzzy cognitive maps. Future Generation Computer Systems 107482.


• J. L. Salmeron and I. Arevalo (2024). Blind Federated Learning without initial model. Journal of Big Data 11:56.


• I. Arévalo and J.L. Salmeron (2024). A chaotic maps-based privacy-preserving distributed deep learning for incomplete and Non-IID datasets. IEEE Transactions on Emerging Topics in Computing 12(1), 357-367.


• J.L. Salmeron, I. Arévalo, and A. Ruiz-Celma (2023). Benchmarking federated strategies in Peer-2-Peer Federated Learning for biomedical data. Heliyon 6(6), E16925.


• I. Arévalo and D. Vukotić (2020). Weighted composition operators in functional Banach spaces: an axiomatic approach. Journal of Spectral Theory 10 (2), 673-701.


• I. Arévalo, MD Contreras, and L Rodríguez-Piazza (2019). Semigroups of composition operators and integral operators on mixed norm spaces. Revista Matemática Complutense 32, 767-798.


• I. Arévalo, R Hernández, MJ Martín, and D Vukotić (2018). On weighted compositions preserving the Carathéodory class. Monatshefte für Mathematik 187 (3), 459-477.


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

Selected conference proceedings

• I. Arevalo, J. L. Salmeron, and I. de la Oliva. Privacy-Preserving Secure Distributed Computer Vision for Malaria Cells Detection, 2024 2nd International Conference on Federated Learning Technologies and Applications (FLTA), September 17 - 20, 2024, Valencia (Spain)


• I. Arevalo, J. L. Salmeron, and I. Romero. Privacy‐preserving distributed learning with chaotic maps, 2024 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS), May 23 - 24, 2024, Madrid (Spain)


• J. L. Salmeron and I. Arevalo. A privacy-preserving, distributed and cooperative FCM-based learning approach for Cancer Research, International Joint Conference on Rough Sets, June 29 - July 3, 2020, La Habana (Cuba)

Datasets

• I. Arevalo and P. Olleros SIESTA Single-Element Density Dataset, Zenodo

Book Chapters

• I. Arevalo and J. L. Salmeron. Chapter 3 - Centralized versus decentralized federated learning, Federated Learning. Editor(s): Rajkumar Buyya, Anwesha Mukherjee, Sajal K. Das.


• J. L. Salmeron and I. Arevalo. Chapter 9 - Secure federated learning with Hindmarsh-Rose encryption, Federated Learning. Editor(s): Rajkumar Buyya, Anwesha Mukherjee, Sajal K. Das.

Dissemination

• ¿Cómo aprende a hablar una máquina?, Retazos de Matemátics y Realidad, UPM, 2026

PhD. Theses

• Privacy-preserving distributed artificial intelligence in connectionism-based models, defended at Universidad Pablo de Olavide on May 3rd, 2024. Advisor: Jose Luis Salmeron.


• Weighted composition operators on spaces and classes of analytic functions, defended at Universidad Autonoma de Madrid on September 15th, 2017. Advisor: Dragan Vukotic.

Teaching

• [Spring 2026] Statistics and Optimization, 1st year Degree in Civil Engineering, UPM.


• [Spring 2025] Programming projects, 2nd year Degree in Computer Science, CUNEF.


• [Fall 2024] Fundamentals of Data Analysis and Research, MsC Data Science, CUNEF.


• [Fall 2024] Neural Networks and Deep Learning, 4th year Degree in Mathematical Engineering, CUNEF.


• [Fall 2024] Programming projects, 3rd year Degree in Computer Science and Business, CUNEF.


• [Spring 2024] Mathematics II, 1st year Degree in Business, CUNEF.


• [Spring 2024] Programming in R, 1st year Degree in Law and Business, CUNEF.


• [Fall 2023] Intro to Programming - Programming in R, 1st year Degree in Data Science and Business, CUNEF.


• [Fall 2023] Programming projects, 3rd year Degree in Computer Science and Business, CUNEF.


• [Fall 2016] Calculus I, 1st year Degree in Mathematics and Computer Science, UAM.


• [Spring 2016] Mathematical Analysis II, 1st year Degree in Physics, UAM.


• [Fall 2014] Mathematical Analysis I, 1st year Degree in Communications Engineering, UAM.

Students

MSc Students

• [Spring 2026] Isabel Jiménez Cortés, Master Thesis titled "Modelado predictivo del precio de los vuelos y análisis de eficiencia aeroportuaria", MSc in Civil Engineering, UPM.


• [Spring 2026] Jinxiang Ye, Master Thesis titled "Fundamentos matemáticos de los sistemas de recomendación", MSc in Advanced Mathematics, UPM.


• [Spring 2025] Sara Pérez, Master Thesis titled "Algorithmic Trading Strategies", MSc in Data Science, CUNEF.


• [Spring 2025] Pablo Oceja, Master Thesis titled "Predicción de la propensión de compra de productos bancarios", MSc in Data Science, CUNEF.


• [Spring 2024] Marina del Hoyo, Master Thesis titled "Recommendation Systems in E-Commerce: An Application for a Digital Retail Business", MSc in Data Science, CUNEF.


• [Spring 2024] Ángel Blanco, Master Thesis titled "Efecto de las técnicas de balanceo en problemas de clasificación desequilibrados", MSc in Data Science, CUNEF.

BSc Students

• [Spring 2026] Ángel de Lucas Miranda, Bachelor's Thesis titled "Análisis topológico de datos y aplicaciones a la propagación de fenómenos virales", Bachelor’s Degree in Mathematics, UPM.

Teaching Resources

• Redes Neuronales (in Spanish): GitHub

Accreditations

• [Summer 2026] Sexenio de investigación (ANECA) (officially recognized six-year research period).


• [Spring 2025] Profesora Contratada Doctora, (ANECA-PEP).


• [Spring 2025] Profesora de Universidad Privada, (ANECA-PEP).

Service

• [March 2025 - ] Elected member of the Claustro Universitario (University Senate) at UPM as representative of assistant professors.


• [March 2025 - ] Elected member of the Comisión Asesora de Estatutos y Reglamentos (Advisory Committee on Statutes and Regulations) at UPM as representative of assistant professors.

Research Projects

• Project PID2024-157080OA-C32 funded by the Spanish Agency for Research (AEI) titled "ACTIVACION TERMOPLASMONICA Y POR CAMPO CERCANO DE DISPOSITIVOS NEUROMORFICOS QUE INTEGRAN OXIDOS CON TRANSICIONES DE FASE Y MATERIALES FERROMAGNETICOS", awarded 143750€.
  PIs: Fernando Ajejas (IMDEA Nanociencia) and Pablo Olleros (CUNEF Universidad). 2025-2029. Role: Main Researcher in the AI workstream.


• Convocatoria de Unidad Cloud UPM de Apoyo a la Investigación funded by Universidad Politécnica de Madrid, awarded 1300€. PI: Irina Arévalo (UPM). 2026.


• BECAS SANTANDER - AYUDA ECONÓMICA PARA PERSONAL INVESTIGADOR POSTDOCTORAL 2025 funded by Banco Santander, awarded 4000€. PI: Irina Arévalo (UPM). 2026.


• MTM2015-65792-P funded by the Spanish Ministry of Economy and Competitiveness titled "DESIGUALDADES Y OPERADORES EN ANALISIS REAL Y COMPLEJO", awarded 29766. PI: Dragan Vukotic (UAM). 2016-2019. Role: Predoctoral Researcher.


• MTM2012-37436-C02-02 funded by the Spanish Ministry of Economy and Competitiveness titled "DERIVADAS E INTEGRABILIDAD DE FUNCIONES ARMÓNICAS Y ANALÍTICAS UNIVALENTES", awarded 29952€.
  PI: Dragan Vukotic (UAM). 2013-2015. Role: Predoctoral Researcher.