Summary
M Marshall is a Linked Data Engineer with 12+ years of experience building data architectures and semantic solutions that enable machine learning and outcome prediction in clinical and imaging domains. He has deep expertise linking EHRs, patient portals, DICOM imaging and research datasets using W3C Semantic Web standards to improve data quality, accessibility and interoperability for clinical decision support. His work at institutions like the Netherlands Cancer Institute and MAASTRO delivered production-grade Semantic DICOM systems and federated SPARQL access that sped radiotherapy data queries by an order of magnitude. More recently he has applied those skills in cloud migrations and ML-related engineering, transplanting pipelines to GCP and building LLM-driven RAG tooling. Comfortable moving between research and production, he combines a PhD in computer science with a pragmatic focus on reusable, auditable data pipelines. An organizer and community leader in HCLS standards, he brings rare domain depth that bridges ontologies, clinical workflows and scalable cloud engineering.
12 years of coding experience
24 years of employment as a software developer
B.A. Computer Science, B.A. Computer Science at University of California, Berkeley
Ph.D. Computer Science, Ph.D. Computer Science at Université de Bordeaux
Dutch