EXPERIENCE

Postdoctoral fellow

Brigham and Women's Hospital - Harvard Medical School • 09/2025-03/2026

As a postdoctoral fellow at the Applied Chest Imaging Lab led by Prof. Dr. Raúl San José Estépar, I developed research on AI-driven pulmonary imaging and deep learning models to predict chronic lung disease progression from non-contrast chest CT. I designed a novel 2.5D Vision Transformer architecture for COPD staging and longitudinal lung-function prediction, developed large-scale training and validation pipelines, and optimized multi-slice fusion strategies that outperformed standard 3D CNN models.

PhD thesis

Universitat Pompeu Fabra - Vall d'Hebrón Institute of Research • 01/2022-07/2025

During my PhD, funded by the Instituto de Salud Carlos III and supervised by Prof. Miguel A. González Ballester and Dr. J. Raul Herance, I led a multi-year project on multimodal, multi-organ phenotyping and risk prediction in type 2 diabetes using PET/CT imaging and clinical biomarkers. I developed AI-driven pipelines integrating liver, heart, and brain imaging with blood-test markers and imaging data to build predictive models of disease progression and patient risk. I created automated tools for organ segmentation, liver-fat quantification, and myocardial insulin resistance assessment, managing large-scale datasets with rigorous standards for reproducibility. I supervised BSc, MSc, and PhD students in study design, analysis, and scientific writing, collaborated across clinical, computational, and imaging teams, and presented findings at international conferences. I also contributed to scientific outreach initiatives for high-school-level audiences. Upon completing my PhD, I transitioned to a postdoctoral role to further develop AI-driven imaging expertise and translational research skills.

Research technician

Vall d'Hebrón Institute of Research • 06/2021-01/2022

As a research technician at the Medical Molecular Imaging Group led by Dr. J. Raul Herance, I supported imaging research in metabolic and cardiovascular disease by building medical imaging PET/CT processing pipelines, performing quality control, and developing computational tools for tissue characterization. I worked closely with multidisciplinary teams of clinicians, imaging scientists, and data analysts to optimize acquisition protocols and streamline workflows. I also supervised MSc students, assisted in BSc student training, and engaged in scientific outreach for high-school students. Following strong performance in this role, I was promoted to a PhD researcher position, enabling me to lead my own research projects within the same group.

MSc thesis

Universitat Pompeu Fabra - Vall d'Hebrón Institute of Research • 09/2020-07/2021

Conducted my master’s thesis under the guidance of Prof. Dr. Miguel A. González Ballester and Dr. J. Raul Herance targeting the characterization of organ-specific metabolic abnormalities in type 2 diabetes using imaging and machine learning techniques. Implemented automated segmentation, quantification and early predictive modeling approaches integrating imaging-derived features with clinical markers. This thesis laid the technical and conceptual foundation for subsequent PhD work on multi-organ phenotyping and predictive modeling.

BSc thesis

Universitat de Barcelona • 01-07/2020

Completed a bachelor’s thesis in radiation and atomic physics under the supervision of Prof. Dr. José M. Fernández Varea. Conducted X-ray and gamma-ray spectral analysis and calibrated a High-Purity Germanium detector to study the physical principles underlying medical imaging and radiation-based cancer treatment. Gained foundational experience in detector physics, quantitative data analysis, radiation–matter interactions, and modeling techniques that later supported advanced work in computational biomedical engineering and medical imaging.

Summer intern in Medical Physics

Catalan Institute of Oncology - Hospital de Bellvitge • 06-09/2016

Completed a summer research internship under the supervision of Dr. Gabriel Reynés-Llompart, working on automated tumor segmentation for Hodgkin’s lymphoma. Developed and evaluated computational methods for PET/CT-based tumor delineation, contributing to improved quantification workflows in radiation oncology. This work led to a first-author publication in Scientific Reports and sparked a long-term interest in combining computational modeling, data analysis, and clinical applications in medical imaging and biomedical engineering.

Mentorship

  • • 3x PhD thesis - 2025 and 2026
  • • 4x MSc thesis - 2022, 2023 and 2024
  • • 2x BSc internships - 2022 and 2023