“The joy of discovery is certainly the liveliest that the mind of man can ever feel”

Our current research is focused on modeling multiomics data to uncover novel insights into human health. 

Key Areas of Research:

• Host-Microbiome Interactions: Understanding the dynamic interplay between the microbiome and its host is a central focus. We use statistical and machine learning models to explore how the microbiome impacts human health, metabolism, and immunity, as well as how the host environment influences the structure and function of microbial communities.

• Applying advanced machine learning algorithms and statistical modeling, for detecting the cell groups and explaining intra-tumoral heterogeneity of glioblastoma using single-cell RNA-seq data. 

# Regularized generalized linear models to analyze the association of microbiome with colorectal cancer. Funding: COST - European Cooperation in Science and Technology. Research institution: Universidade NOVA de Lisboa. 

# Statistical and machine learning techniques in human microbiome studies (ML4Microbiome), CA18131. 

#Towards personalized medicine: predicting disease progression of MS patients from trajectory data (R-9635). Research Institution: Biomedical Research Institute, UHasselt. Funding: Hasselt University, Belgium. 

# Researcher Mental Health (ReMO), CA19117.