Tudor Groza is an experienced computer scientist with a background in knowledge representation, ontologies, natural language processing, and artificial intelligence in precision medicine. His work spans across various dimensions of the research – clinical care continuum, from devising algorithms to support clinical decision-making in the rare disorders field to standardization of clinical terminology and integration with national public and private health systems. Over the course of the last ten years, Tudor focused on contributing to the clinical phenotyping community, both as an academic as well as an entrepreneur, by building deep phenotyping tools to aid the decision-making process in clinical genomics and primary care.
In an effort to enable harmonized phenotype acquisition, Tudor has contributed to various terminology standardization initiatives, including: co-leading the Phenotype Representation group (GA4GH Clinical Data and Phenotype work stream) or co-leading the Data Sharing group within the Undiagnosed Diseases Network International. Currently, he is a member of the Primary Care and Integrating New Technologies for the Diagnosis of Rare Diseases task forces of the International Rare Diseases Research Consortium. From an industry perspective, as former CTO of Genome. One, Tudor led the Personal Health Applications business unit through a clinical accreditation process and the development of the first patient self-phenotyping platform for large-scale precision medicine in collaboration with the largest rural healthcare provider in the US. In 2018, he co-founded Pryzm Health with the goal to reduce the diagnostic odyssey of patients susceptible of rare disorders by introducing phenotype-driven patient stratification methods in primary care.
Currently, he leads the Phenomics team at the European Bioinformatics Institute where he aims to contribute to the acceleration of translational and clinical applications of genomic technologies by creating comprehensive disease models using cross-species phenotype data.