Angelica Aviles Rivero

Dr Angelica Aviles Rivero is a faculty member in the Department of Mathematics at the University of Cambridge. Her research focuses on computational mathematics and machine learning, particularly in the area of Cambridge Image Analysis. Her work involves developing data-driven algorithmic techniques to enable computers to gain high-level understanding from large datasets, with the goal of supporting user decision-making. Her research is grounded in mathematical modeling and machine learning methods, with applications to real-world problems. She is affiliated with the Faculty of Mathematics and can be contacted via email at ai323@cam.ac.uk.

Angelica I. Aviles-Rivero Yau is a researcher in Computational Mathematics, Applied Mathematics, and Machine Learning. Her work focuses on developing advanced algorithms for medical image analysis, time series forecasting, and inverse imaging problems. She has contributed to projects involving machine learning for medical imaging, such as DiffMIC and Contrastive Registration for Unsupervised Medical Image Segmentation. Her research also includes semi-supervised learning frameworks and neuro-recurrent-vision approaches for robotic-assisted surgery. Aviles-Rivero Yau's publications highlight her expertise in integrating mathematical modeling with machine learning techniques to address complex challenges in healthcare and computer vision.