Computational Precision Health

The UCSF UC Berkeley Joint Program in Computational Precision Health (CPH) is building a new discipline at the intersection of artificial intelligence and machine learning, new statistical method, clinical and public health practice, and equity. The program leverages the expertise in computer science and statistics at UC Berkeley, the health data, excellence in clinical practice and bioinformatics at UCSF, and the commitment to population health at both institutions to create a first-in-kind interdisciplinary PhD training program. 

Students in the PhD in Computational Precision Health develop skills and expertise in both the computational sciences (machine learning and AI, natural language processing, statistical inference and modeling, data standards, parallel computing and data at scale, etc.) and health sciences (clinical decision sciences and cognitive informatics, clinical delivery, clinical research, implementation science, health information policy, etc.)

Students develop the ability to work in interdisciplinary teams from ideation to development, testing, and validation in the real world. Coursework is complemented by extensive and early interaction with world-class faculty – through research rotations, seminar series, and practicums – at the intersection of computation and health, and will develop proficiency in cross-disciplinary research and communication. A focus on diversity, equity and inclusion, human-centered design accommodating diverse users, and the ethical implications and societal impacts of the work are embedded throughout the program.

Faculty

CPH faculty are members of the Joint Augmented Graduate Group in Computational Precision Health. There are currently more than 60 faculty members: four with primary appointment in CPH, with others from multiple departments across UCSF and UC Berkeley. UCSF faculty hail from all UCSF clinical sites, reflecting the diversity of populations and care settings across San Francisco.