Introduction

Dr. Marcos Matabuena is an incoming Assistant Professor at Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), with more than eight years of experience in machine learning, biostatistical theory and methods, biomedical applications, and software development. His research focuses on functional data analysis, survival analysis, and conformal prediction, motivated by digital health data from continuous glucose monitoring (CGM) wearables and electronic health records (EHRs).

He has contributed pioneering ideas including the concept of glucodensity, functional representations of wearable data, and new statistical methods in metric spaces—such as conformal prediction and biclustering—to model complex, individualized digital health trajectories. His work spans applications in aging, ALS, diabetes, and cancer, and his future agenda aims to advance statistical AI methods for digital health and integrate wearable data with genetic information for precision medicine.