Tibor V Varga

Tibor V Varga

Associate Professor

  • Øster Farimagsgade 5

    1353 København K

  • Source: Scopus
20122024

Research activity per year

Personal profile

Knowledge of languages

English, Hungarian

Primary fields of research

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

Fields of interest

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.

CV

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.

 

Introductory remarks on publicationslist

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

 

Education/Academic qualification

Medical Sciences, Genetic Epidemiology, PhD., Lund University

Award Date: 28 Apr 2016

Nutritional Sciences, MSc., Semmelweis University

Award Date: 13 Jun 2013

Biology, BSc., Eotvos Lorand University

Award Date: 26 Jun 2009

Keywords

  • Faculty of Health and Medical Sciences
  • machine learning
  • artificial intelligence
  • social inequality
  • Biostatistics
  • epidemiology
  • Causality
  • health equity
  • biomarkers
  • fairness
  • social epidemiology
  • missing data
  • simulation
  • diabetes
  • mental health
  • outcomes
  • Academic writing
  • algorithmic fairness
  • machine learning fairness
  • Prediction Models
  • prediction

Collaborations and top research areas from the last five years

Recent external collaboration on country/territory level. Dive into details by clicking on the dots or