Arriel Benis

Dr. Arriel Benis’s research integrates artificial intelligence (AI), biomedical and health informatics (BMHI), digital health and digital epidemiology, data science, and biomedical engineering (BME) to address critical challenges in healthcare and biomedical discovery. His work focuses on developing data-driven methods that improve population health, advance precision medicine, and support sustainable healthcare systems. His research spans four primary areas: AI and Predictive Modeling, Biomedical Informatics and Digital Health, One Digital Health and Sustainability, and Education and Workforce Development.

AI and Predictive Modeling: Dr. Benis develops predictive models and clinical decision-support systems through the analysis of large-scale clinical, biomedical, and social datasets. His work emphasizes data interoperability and adherence to FAIR (Findable, Accessible, Interoperable, Reusable) data principles. These approaches enable the development of intelligent systems to predict disease progression, optimize treatment strategies, and support personalized patient care.

Biomedical Informatics and Digital Health: His research integrates heterogeneous data sources (including electronic health records (EHRs), patient-reported surveys, wearable sensors, and digital communications) to improve clinical workflows and support patient-centered digital health innovation. This work facilitates multicenter studies, advances knowledge discovery, and informs healthcare policy while promoting innovation in biomedical and health informatics.

One Digital Health (ODH) and Sustainability: Dr. Benis advances the One Digital Health framework, which links One Health and Digital Health to address complex global health and environmental challenges. His work develops integrated strategies that combine digital health technologies with environmental monitoring to support climate-responsive, sustainable healthcare systems.

Education and Workforce Development: Dr. Benis contributes to strengthening the biomedical workforce through interdisciplinary training in AI, informatics, and digital health. He leads international educational initiatives, including the MIMO (Medical Informatics and Digital Health Multilingual Ontology) project, aimed at developing the next generation of researchers and practitioners in biomedical data science and digital health.