Human Genomics and Complex Diseases

Characterization of genetic variants associated with complex diseases using statistical methods, probabilistic modeling, and general machine learning techniques, including polygenic risk prediction, population structure analysis, and mining of large genomic cohorts.

Systems Biology and Complex Diseases

Mathematical and computational modeling of biological networks, inference of gene and regulatory interactions from large-scale omics data, and identification of emergent patterns using machine learning and graph theory.

Bioinformatics and Multi-Omics Integration

Development of reproducible pipelines, software tools, and biological databases for the storage, curation, integration, and analysis of genomic, transcriptomic, proteomic, and phenotypic data. Application of general machine learning approaches for biomarker discovery, molecular stratification of complex phenotypes, and support for data-driven precision medicine.