Angelica I Aviles Rivero

Senior Research Associate, University of Cambridge

Angelica’s research focuses on the intersection of computational mathematics, inverse problems, and machine learning, with a strong emphasis on addressing large-scale, real-world challenges. She develops novel algorithmic approaches capable of processing vast amounts of data, particularly by integrating machine learning techniques with knowledge-driven models. Her work centers on hybrid techniques that combine data-driven insights with physical and geometric constraints, such as variational models enhanced by machine learning, enabling more efficient and accurate analysis of large and complex data. 

Her research interests include, but are not limited to:  Applied Mathematics, Computational Mathematics,  Inverse Problems, Computer Vision, Medical Image Analysis, Machine Learning, Graph Learning and Hybrid Models.