Evelyn Patricia Gutiérrez Ayala

In my thesis, I focus on the study of registration between 3D models and thermal information to create quantitative metrics for chronic wound assessment. I am particularly interested in the use of affordable and portable devices; and the use of 3D computer vision to provide an affordable and remote wound assessment tool. As a result, I have developed and implemented an automated system for acquiring 3D thermal models in clinical environments. All my algorithms are initially developed in Python. The first POCs was developed in Matlab and RMarkdown. In 2023, an android smartphone application has been finalized and is currently in alpha stage. Activities performed during the PhD - I researched algorithms for the registration of thermal imaging to 3D models. - Proposed and implemented a process for creating a 3D thermal model using portable and low-cost devices. - Planning and execution of data acquisition for a longitudinal pilot study in France and Peru. - Design and implementation of dashboards for tracking longitudinal data acquisition. - Implementation of online visualization tools for interaction with 3D thermal models. - I supervised and mentor 3 undergraduate students and 1 android developer. Software used: R, Python

My master's thesis, "Estimation of the disease prevalence when diagnostic tests are subject to classification error: Bayesian Approach" won the 2016 Graduate Student Research Support Program (PAIP) award. My dissertation was unanimously qualified as "outstanding".