Strategy | Data Architecture | Knowledge Representation | Applied AI | Scientific & Technical Leadership
I am a computer scientist, data scientist, and interdisciplinary technical leader whose work has focused on turning complex data and scientific knowledge into practical systems, research programs, and organizational capabilities. My career spans biomedical informatics, predictive modeling, semantic technologies, data architecture, artificial intelligence, software engineering, systems engineering, and the development of interdisciplinary data-science programs.
I have worked across industry, government, academia, and healthcare, including MITRE, MIT, GE Global Research, Harvard Medical School/Massachusetts General Hospital, Rensselaer Polytechnic Institute, the University of the Virgin Islands, and numerous life-sciences organizations.
Selected examples of work connecting data, science, technology, and organizations to create practical research, healthcare, and educational impact.
BioPAX
Helped create and advance an international standard for exchanging biological pathway data, secured funding, selected enabling technology, and built a worldwide network of stakeholders and contributors.
Predictive Medicine
Applied neural-network modeling, predictive analytics, and biomedical informatics to treatment response and other healthcare problems. Research on major depressive disorder led to two U.S. patents covering treatment selection and prediction of therapeutic outcome.
MITRE
Led development of an influenza ontology supporting U.S. research and surveillance and founded an ontology-evaluation research program that developed the Generalized Ontology Evaluation Framework (GOEF) and received NIST support.
UVI Data Science
Conceived, designed, and implemented the University of the Virgin Islands undergraduate Data Science Minor and Certificate, creating an interdisciplinary curriculum accessible to students across the university.
I advise leaders, technical teams, researchers, educators, and organizations working through complex data, technology, research, and program-development decisions. My approach combines technical depth, interdisciplinary perspective, and practical experience translating between scientific, technical, organizational, and stakeholder communities.
Data science, statistical analysis, predictive modeling, machine learning, data architecture and integration, data quality and governance, and the responsible application of AI to complex scientific, healthcare, government, and organizational problems.
I work with organizations to develop data and technology strategies aligned with their scientific, operational, and business objectives. Areas include data architecture and integration, governance and quality, analytics and AI strategy, biomedical and scientific data, interoperability, knowledge representation, and development of new technical programs and partnerships.
I develop and deliver technical education for university, government, nonprofit, and professional audiences, including data science, AI, data literacy, biomedical informatics, semantic technologies, and emerging technologies.