Belén Ríos Sánchez, PhD, is Permanent Professor at the Department of Applied Mathematics to ICT at the School of Computer Engineering (E.T.S.I. Informáticos) at  Technical University of Madrid (UPM) and researcher at   the Medical Data Analysis laboratory (MEDAL) at Center for Biomedical Technology (UPM). Her main research interest include Image Processing and Pattern Recognition using Machine Learning techniques. Over the past decade, she has used convolutional neural networks for various tasks such as object detection and segmentation, as well as the extraction of distinctive patterns. While much of her research focuses on image-based biometrics, she has also extended her expertise to the field of precision medicine, applying advanced data processing and machine learning techniques to improve disease diagnosis and treatment. She has a M.Sc in Computer Science Engineering, a M.Sc in Telecommunications in the speciality of Signal, Systems and Radiocommunications, and a PhD in Computer Science. Additionally, in 2011, she was awarded a doctoral fellowship through the European Erasmus-BEAM program to carry out a 12-month stay at the Computer Vision and Pattern Analysis, Ishikawa Lab, Waseda University, Tokyo, Japan. This stay provided her with extensive knowledge in image processing, graph-based algorithms, and machine learning techniques.

Prof. Ríos research experience includes the participation in more than 25 competitive research and innovation projects funded by public, at national (Spain) and international level (FP7/H2020/EIT Health) level, and private entities. She is author/co-author of 5 articles in JCR-indexed journals and 1 book chapter. She has also presented about 20 communications related to her research in international conferences.

Regarding her teaching experience, she has taught over 400 hours in official undergraduate and postgraduate programs, as well as specific training courses for private company staff. She has been teaching in subjects such as Calculus, Discrete Mathematics I and II, Mathematical Method, Mathematical Modeling or Programming for Data Science in several degrees such as Computer Science BSc, Computer Science and Mathematics BSc, Biomedical Engineering BSc, Telecommunication Technologies and Services Engineering BSc, Digital Innovation MSc or Data Science MSc. Additionally, she has supervised 18 final degree projects (BSc and MSc).