The Duke Computational and Digital Health (CDH) Certificate Program
Bridging Engineering, AI, Ethics, and Healthcare for Equitable Innovation
The Duke CDH Certificate Program offers interdisciplinary training in computational modeling, AI, wearable sensor technologies, and digital twins—all with a strong foundation in bioethics and clinical translation. The program is designed to equip students with the technical and ethical expertise to transform modern healthcare through data-driven and patient-centered solutions.
(Duke NetID required)
Preparing Leaders in Digital Health
As healthcare rapidly shifts toward personalized, data-driven approaches, there is an urgent need for professionals who understand both the computational tools and the ethical, clinical, and deployment challenges they bring. This program meets that need by integrating engineering, medicine, and ethics into a cohesive, rigorous certificate experience.
Trainees Are Drawn from Duke Programs
As a non-admitting certificate program, the CDH Certificate draws students from existing pre-doctoral programs at Duke across Engineering. Please note, all trainees must meet the degree requirements of their home department and the university.
Acceptance Criteria
Students must:
- Be enrolled in a Duke graduate program in Engineering, Arts & Sciences, or Medicine.
- Demonstrate interest in computational or digital health technologies.
- Be actively involved in research aligned with CDH themes.
- Participate in the required Communities of Practice (CoP) events during the program.
Curriculum
The curriculum combines technical, biomedical, and ethical training with flexibility to support a wide range of student backgrounds. Review the curriculum.
Communities of Practice
A central component of the Computational and Digital Health (CDH) Certificate is active participation in Communities of Practice (CoP). These communities bring together students, faculty, postdoctoral fellows, and industry partners to engage in sustained dialogue on emerging topics in computational and digital health. CoPs are designed to foster both technical expertise and ethical awareness while cultivating the professional networks that support leadership in this rapidly evolving field.
CoP sessions incorporate active deliverables, ensuring that participants move beyond discussion to applied learning. Examples include written reflections on CDH technologies, research communication exercises (such as 3 Minute Thesis–style presentations), networking with other students during the year, and engagement through blogs, social media, or other public-facing platforms. These activities are intended to strengthen critical thinking, refine the ability to convey complex ideas to diverse audiences, and highlight the societal and ethical dimensions of digital health research.
CoPs are offered several times each year, and students in the certificate program are expected to participate in at least five sessions over the course of their studies. Through this requirement, trainees will engage with cutting-edge issues such as algorithmic bias, wearable performance in diverse populations, and secure data use, while also developing the collaborative, communicative, and ethical capacities essential for future careers in computational and digital health.
(Duke NetID required)
