I’m a mathematical engineer with an MSc degree in applied mathematics at the University of Chile. My research interests lie in Inverse Problems, PDEs and Deep Learning. I like to apply my knowledge in real-world problems, especially in those arising from the biomedicine area and medical imaging.
Currently, I’m working as a young researcher at the Millennium Nucleus for Cardiovascular Magnetic Resonance, where the goal of the project I’m carrying out is to reconstruct strain parameters from cine-MRI sequences with an image registration approach based on physics-informed neural networks. These strain parameters are, nowadays, being used to make better diagnosis and prognosis of heart’s diseases.
In my leisure time, I like to learn new things about deep learning, play the piano, play football, take a walk with Brunildo and listen to new musicians.
MSc in Applied Mathematics, 2020
Universidad de Chile, Facultad de Ciencias Físicas y Matemáticas
Civil Mathematical Engineering, 2020
Universidad de Chile, Facultad de Ciencias Físicas y Matemáticas
BSc in Engineering, with specialization in mathematics, 2018
Universidad de Chile, Facultad de Ciencias Físicas y Matemáticas
Minor in Quantum Physics, 2018
Universidad de Chile, Facultad de Ciencias Físicas y Matemáticas
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Obtain cardiac strain parameters from cine-MRI sequences with physics-informed neural networks. Responsibilities include:
Stability for an inverse problem related to a 2D model of Light Sheet Fluorescence Microscopy based on heat equation and extension of the direct model to the 3D case.