Summary
Xiao Da is a scientist and imaging-focused data strategist with 11+ years applying advanced image processing, machine learning, and high-performance/cloud computing to clinical trials and neuroimaging research. She has built end-to-end multimodal imaging platforms and scalable ETL pipelines for MRI, PET, MRS and microscopy data, translating biomarkers into regulatory-ready outcomes including FDA Breakthrough Device support and a pivotal Phase 3 trial. Her work spans neurodegeneration, oncology, and psychiatric disorders—developing reproducible pipelines (Docker/HPC/AWS), novel MRS quantification approaches, and AI models that predict clinical trajectories and streamline patient selection. A collaborative leader and mentor, she blends hands-on algorithm development with trial operations, vendor KPIs, and cross-disciplinary partnerships to keep QC-failure rates under 5%. Notably, she validated spectral fitting across species (macaque to human) to improve GABA quantification reproducibility, highlighting a rare combination of translational rigor and production-scale engineering.
11 years of coding experience