Machine Learning Theory and Methods
Design and analysis of machine learning algorithms, not focused on a specific, immediate biomedical application. This line of work includes research on deep learning, quantum machine learning, quantum-inspired techniques, and, previously, on ensemble learning and image analysis.
Bioinformatics Methods
Developing novel methods for analyzing biological data, typically for uncovering the molecular underpinnings of phenotypic differences. The main theme is the focus on the networked nature of biological systems. Recently, we also focused on group testing.
Applied Bioinformatics and Biomedical Data Science
Analyzing biomedical data towards gaining a better understanding of human health and its disorders.
Current focus is on analyzing human microbiome. Past focus was on healthy and impaired wound healing, and on analyzing divergence of protein structure as its genetic sequence changes.
