Mauro Leidi

Research Interests. My primary research interests lie in the dynamic intersection of machine learning, computer vision, and biomedical image processing, with a focus on the evolving landscape of AI integration within clinical medicine. Specifically, I am dedicated to advancing my expertise in leveraging machine learning applications to address the limitations inherent to MRI and harness the full potential of this technique.

Furthermore, I am enthusiastic about tracking the latest advancements in various domains of deep learning and eagerly seek opportunities to implement these developments in real-world applications. My passion for exploring the frontiers of AI and its potential to revolutionize medical diagnostics and treatment motivates my research endeavors.

Short Bio. I am a machine learning enthusiast, driven by a profound interest in computer vision and the plethora of its potential applications. My journey in the field of technology began in Lugano, Switzerland, where I successfully completed my high school studies before embarking on my academic pursuits at EPFL in Lausanne. Initially studying microengineering during my Bachelor's, I found myself increasingly drawn to the remarkable advancements in Data Science, which led me to transition my major to Data Science.

In 2023, I completed my Master's degree, culminating my academic journey at EPFL with a Master's thesis conducted at Huawei's Research Center in Munich. My initial encounter with the Mattech Lab was during my semester project in 2022, where I gained valuable experience working with OCT scans and MAIA images, solidifying my interest in the realm of biomedical imaging.

I rejoined the MatTech lab in October 2023 as a Research Scientist, focusing on the cutting-edge 'Kick-fMRI' (Kids Compliant fMRI) project. This pioneering initiative aims to revolutionize fMRI for pediatric use, addressing the challenges posed by motion artifacts in young subjects. By developing the innovative Ki-Ck fMRI technique, tailored to reliably capture and correct for motion artifacts in children as young as 6 years old, we are opening new, exciting possibilities in pediatric neuroscience.

Affiliations:

1. School of Engineering, Institute of Systems Engineering,  HES-SO Valais-Wallis, Route de L’industrie 23, Sion, Switzerland 

2. The Sense Innovation and Research Center, Lausanne and Sion, Switzerland 

3. Department of Data Analysis, Ghent University, Ghent, Belgium

4. Graduate School for Cellular and Biomedical Sciences (GCB), University of Bern, Mittelstrasse 43, CH-3012 Bern, Switzerland