BCAM’s researcher Verónica Álvarez Castro wins the Frances Allen Award from the Spanish Association for Artificial Intelligence for her Doctoral Thesis

• Verónica Álvarez Castro's thesis, 'Supervised Learning in Time-dependent Environments with Performance Guarantees', has been awarded the first prize of the 2024 call.
• The Frances Allen Awards aim to promote the visibility and recognition of women in the field of artificial intelligence.
   

Verónica Álvarez Castro, researcher at BCAM, Basque Center for Applied Mathematics, has won the Frances Allen Award of the Spanish Association for Artificial Intelligence (AEPIA) for her doctoral thesis 'Supervised Learning in Time-dependent Environments with Performance Guarantees'. This prize, awarded in the 2024 call, recognizes the excellence and impact of her work in the field of AI.

This recognition highlights not only the exceptional quality of her research, but also her significant contribution to the advancement of knowledge in the area of supervised learning in time-dependent learning in time-dependent environments with performance guarantees. 

The Frances Allen Awards, named in honor of the influential computing pioneer Frances Allen, aim to promote the visibility and recognition of women in the field of artificial intelligence. The award for Verónica Álvarez Castro's PhD Thesis highlights her outstanding role in the AI scientific community and her contribution to the empowerment of women in this constantly evolving field. In addition, it has an endowment of 350 euros.

Alvarez Castro's research establishes methodologies for supervised learning from a sequence of problems that change over time. These changes over time are common in multiple applications such as spam filters, fraud detection and energy consumption prediction. For example, in the energy prediction problem, consumptions, price and generation are constantly changing over time due to variations in habits and weather.  Her thesis establishes methodologies that effectively exploit information from all problems received over time, adapt to changes, and provide theoretical performance guarantees.

These contributions offer theoretical and practical advances in the field of machine learning and artificial intelligence. Veronica's contributions during the thesis have been published in the most prestigious journals and conferences in the field, such as “Probabilistic load forecasting based on adaptive online learning” published in IEEE Transactions on Power Systems, no. 4, 3668-3680, 2021; “Minimax classification under concept drift with multidimensional adaptation and performance guarantees” published in the International Conference on Machine Learning (ICML), pp. 486-499., 2022; and “Minimax forward and backward learning of evolving tasks with performance guarantees” published in Advances in Neural Information Processing Systems (NeurIPS), pp. 65678-65702, 2023. 

Graduated in Mathematics from the University of Salamanca in 2019, Verónica Álvarez Castro is currently a postdoctoral researcher in the Machine Learning line at BCAM. This is not the first award she has received, as her paper 'Probabilistic Load Forecasting Based on Adaptive Online Learning' published in IEEE-Transactions on Power Systems together with her thesis directors Santiago Mazuelas and José Antonio Lozano, was awarded Best Applied Contribution with an Impact on the Social Scope, Innovation or Knowledge Transfer in the Field of Statistics at the Sociedad de Estadística e Investigación Operativa (SEIO)-Fundación BBVA Awards in 2022.

“I am grateful to have received the prestigious Frances Allen Award, which I know will significantly boost my career in the field of Artificial Intelligence. This recognition not only values my dedication and work, but also highlights the importance of diversity and inclusion in the scientific community. I am excited about the opportunities this award opens up for me and look forward to taking full advantage of them as I continue to advance my research and try to contribute to the advancement of AI. Once again, I want to express my sincere appreciation for this honor and for the continued support of those who have made this achievement possible,” states Álvarez Castro.