The Health Data Science Research and Learning Cluster (HDS RLC)’s focus is on computing systems and approaches, data security technology, and analytic drivers to advance research on health data. Examples of foci areas include secure virtual computing platforms for advancing machine learning capabilities and analysis on protected health information (PHI) data.
This new cluster will serve as a hub for the community with bi-weekly meetings, short lectures and thematic discussion groups, and will serve as a home for the interdisciplinary scholars in computer science, health informatics, and data science to develop next-generation systems for health data science research. Membership is open all members of the UC Davis Health and UC Davis communities.
Reasons to join the cluster include:
Learning the challenges and opportunities in systems engineering and applied data sciences on health data;
Design, develop and use scalable and powerful computing systems that allow for data integration, analysis and sharing of protected data;
Discuss models and systems for advancing research computing and data sharing in health informatics;
Access DataLab and other health and research computational resources;
Connect with and receive advice from diverse peers across UC Davis and UC Davis Health campuses;
Open source and reproducible data enthusiasts and health-hackers welcome.