Groups
We pioneer the fusion of Machine Learning and Data Integration to revolutionize human and environmental health research. We actively advance scientific discovery, grounding our AI in explainability and championing reproducible research methodologies.
We harness the power of multi-omics data integration to unravel chemical-based molecular perturbations. By pioneering cutting-edge methods for pathway enrichment and chemical grouping, we push the boundaries of omics data application in regulatory risk assessment and decision-making, while adhering to the FAIR principles.
With an emphasis on mechanistic understanding, we develop toxicokinetic models elucidating chemical behavior in aquatic and terrestrial organisms. We also aim to minimize reliance on animal testing by developing predictive tools and in vitro - in vivo extrapolation techniques.