English, Hungarian

artificial intelligence, machine learning, predictive statistics, social inequalities, health justice, causal inference, biomarkers.

Key interests

• Artificial Intelligence, Machine learning
• Algorithmic Fairness
• Predictive statistics
• Health equality, health equity, health justice

Brief CV

Tibor obtained his BSc in Biology (2009, ELTE, Hungary), MSc in Nutritional Sciences (2013, Semmelweis University, Hungary), and PhD in Genetic Epidemiology (2016, Lund University, Sweden) and is currently working as an Associate Professor at the University of Copenhagen.

During his PhD, postdoc, and Assistant Professorship, Tibor worked primarily with metabolic diseases, cardiovascular genetics, genetic association studies, gene x environment interactions, and prospective omics analyses. He used various statistical and machine-learning techniques to gain information on associations and predictive biomarkers for various metabolic disease outcomes. 

In his current Associate Professorship, Tibor is working on how to use AI on prospective, life-course big data to promote health equity.

It is hard to keep track and update CVs at so many different locations - In case you are interested in my profile as a researcher, please visit my Linkedin profile, my ORCID portfolio, or the list of my published papers on PubMed.

Please see my ORCID portfolio, or the list of my published papers on PubMed.