Tibor V Varga

Tibor V Varga is an Associate Professor at the Department of Public Health, University of Copenhagen, where he is affiliated with the Copenhagen Health Complexity Center. His work focuses on applying artificial intelligence and machine learning techniques to address health equity issues through analysis of life-course big data.

Education:

• PhD in Genetic Epidemiology, Lund University (2016)
• MSc in Nutritional Sciences, Semmelweis University (2013)
• BSc in Biology, Eotvos Lorand University (2009)

Tibor's research spans the intersection of artificial intelligence, epidemiology, and social determinants of health. His primary areas of interest include machine learning, predictive statistics, causal inference, and biomarker analysis with a focus on addressing social inequalities and promoting health justice. He has particular expertise in applying algorithmic fairness principles to health data analysis, ensuring that AI-driven health solutions do not exacerbate existing health disparities. His work often involves large-scale data analysis to identify patterns that can inform public health interventions aimed at reducing health inequities across diverse populations.

His recent publications demonstrate a clear trajectory toward using AI to address complex health equity challenges. The articles span diverse topics including racial disparities in diabetes technology, psilocybin therapy for alcohol use disorder, European health data infrastructure, and the relationship between digital behaviors and health outcomes. This breadth reflects his interdisciplinary approach, combining computational methods with public health applications to tackle issues at the intersection of technology, society, and health.

Tibor actively contributes to methodological discussions in scientific publishing and has co-authored works on improving the efficiency of biomedical publishing processes. His research has received attention in multiple news outlets and academic platforms, indicating the relevance and impact of his work in both academic and public spheres.

His collaborative network extends across Europe and beyond, working with researchers from various disciplines to address complex health challenges through data-driven approaches. This international collaboration is particularly evident in his work related to the European Health Data Space initiative.