Translational Bridge

Our translational mission is to connect AI/ML innovation with everyday research and clinical decision-making. In practice, this means designing methods that are not only technically strong, but also interpretable, deployable, and compatible with real-world constraints in genetics clinics and biomedical laboratories. We work at the interface of computational science, genomics, and patient care so that advanced models can be used responsibly by clinicians, not just evaluated in idealized settings.

This bridge is especially important in rare disease and neurodevelopmental research, where clinicians need timely and evidence-based guidance from complex genomic data. Through projects such as AI-MARRVEL and related diagnostic workflows, we support variant prioritization, phenotype-guided interpretation, and evidence integration across databases, model organisms, and literature. Our autism and neurological disease efforts follow the same translational logic: combine large-scale data science with biologically grounded interpretation to improve diagnosis, stratification, and treatment-oriented discovery.

We maintain close collaboration with clinical teams and research partners, including Texas Children’s Hospital, Baylor College of Medicine, and broader undiagnosed disease networks, to ensure iterative improvement from real use. This collaboration-driven model supports secure data handling, continuous model refinement, and practical implementation pathways that move computational advances from development into measurable patient impact.