Jaime Barranco

Research scientist
University of Lausanne (UNIL) and Lausanne University Hospital (CHUV)

Lausanne University Hospital
, Radiology Department (CHUV)

University of Lausanne, CIBM Center for Biomedical Imaging


Email: jaime (dot) barranco-hernandez (at) chuv (dot) ch
Postal address: Centre de Recherche en Radiologie (RC7), Rue du Bugnon 46, CH-1011 Lausanne
Office: Rue Centrale 7, 4th floor, CH-1003 Lausanne

Research Interests

Biomedical image processing, machine and deep learning techniques, and web-platform implementation. In the “A-eye” project, funded by the Gelbert Foundation, we aim at a breakthrough towards AI-system for the assessment of Magnetic Resonance Imaging of the eye. The automated analysis of eye structures would establish the basis to study how different structures degenerate during disease, or in the field of personalized medicine, to build up targeted and accurate surgery plans. The project will be led under the supervision of Dr. Bach Cuadra (CIBM SP CHUV-UNIL section) and Prof B. Franceschiello (HES-SO Valais-Wallis) and in collaboration with Sönke Langner and Oliver Stachs, experts in eye MR microscopy and ophthalmology at University Medical Center Rostock, Germany, and Prof. Raphael Sznitman (ARTORG Center & Center for Artificial Intelligence in Medicine, Insepital, Bern).

Short Bio

I was born in Madrid, where I studied my Bachelor’s and Master’s degrees in Telecommunications engineering at Universidad Politécnica de Madrid (UPM).

I took the bachelor’s expertise in image and sound technologies, where I learned digital image and audio processing. Then, in the second year of the master’s degree, I worked in machine learning and multimedia data science branch, where I developed machine and deep learning techniques applied to audiovisual systems. My master’s thesis was related to segmentation of moving objects, where the goal was to find cases in which the most common objective metric f-score may not be adequate to evaluate the quality, and draw conclusions on developing a new metric that takes into account subjective evaluation. I developed a tool using Matlab for subjective evaluation of foreground segmentation algorithms, which is still available at the following link: SETForSeQ.

I have also 1 and half year experience as software engineer for NexPlayer, a video streaming company in Madrid. There, I used to develop wrappers connecting the native players (coded in C++, Java, Objective-C, Javascript, and C) with the Unity layer (coded in C#), allowing us to build for five different platforms: Android, iOS, Windows, MacOS, and WebGL.