Academic Background

Throughout my educational path, I have developed a deep expertise in the field of artificial intelligence. My international academic trajectory has not only equipped me with a solid foundation in AI but has also nurtured my passion for continuous learning and self-improvement. Alongside the formal courses I took, I also embarked on a self-taught learning journey, taking the initiative to explore various AI-related courses independently. This self-driven approach allowed me to enhance my knowledge and skills beyond the boundaries of the traditional curriculum.

Formal Education

Photo of Henry Areiza at the University of Rennes

Ph.D. in Computer Science

Université de Rennes

2019 - 2023

Thesis: Analysis of thoracic and intra-gastric cardiac vibration signals for the monitoring of heart failure

The main objective of this thesis was to propose signal acquisition and processing methods to make the best use of inertial units in the monitoring of patients with heart failure (HF), by efficiently exploiting multimodal information from cardiac vibration signals (CVS). Two novel approaches were proposed in this context: 1) the evaluation of the feasibility of acquiring longitudinal CVS using an intra-gastric implant in a preclinical animal experimentation setup, and 2) the development of a cardiac signal acquisition system to preliminarily assess the feasibility of automatically detecting cardiorespiratory events on-the-edge using a MEMS sensor with an embedded machine learning core (MLC).

M.Sc. in Automation and Industrial Control

ITM University Institution

2017 - 2019

Thesis: Objective selection of relevant MRI sequences for breast cancer diagnosis using MKL and SVM

In this thesis, a method based on the use of multiple kernel learning (MKL) and support vector machines (SVM) is proposed to objectively and automatically select the most relevant MRI sequences for the diagnosis of breast cancer, through the penalty of the weights associated with each one of the kernel matrices that represent the magnetic resonance imaging (MRI) sequences.

B.Eng. in Electronic Engineering

ITM University Institution

2013 - 2017

The Electronics Engineering program at ITM develops competencies to provide solutions in the area of automation and industrial control using programmable devices, manage data networks, and advise design projects with embedded systems. It also trains students to develop computational systems for the capture, management, processing and analysis of data, generating new information for decision making and problem solving in different contexts using artificial intelligence techniques.