Research Areas

AI Models and Algorithms for Systems and Network Medicine

We develop computational methods for systems and network medicine applications. Problems we are working on include inference of gene regulatory networks, mining of  pathomechanisms in protein-protein interaction networks, dimensionality reduction for high-dimensional molecular data, and detection of differentially abundant cell populations in single-cell data.

Key Publications

Meta-Scientific Questions in Bioinformatics

We cary out research meta-scientific topics in computational biomedicine. Such topics include (lack of) reproducibility of biomedical AI systems, the effect of data leakage on such systems, and the impact of various forms of biases on data-driven methods in network and systems biology.

Key Publications

Privacy-Aware Methods in Computational Biomedicine

We develop privacy-aware methods for problems in computational biomedicine, mainly making use of federated learning. Problems we are working on include federated genome-wide association studies and privacy-aware computation of differentially expressed genes from distributed gene expression data.

Key Publications

Applied Combinatorial Optimization

We develop graph-based algorithms for applied combinatorial optimization problems. Problems we are working on include the computation of distances between graphs and trees and enumeration of matchings and paths under diversity constraints.

Key Publications