The Fellowship proposals involve diverse approaches applicable to healthcare, including machine learning, computer science, robotics, language technologies, computational biology, electrical and computer engineering, economics, psychology, sociology, public policy, business administration, law, human-computer interaction, and statistics. Projects can be at any stage, from initial to mature.
The goals of the Fellowship program include fostering interdisciplinary research ideas, increasing student involvement with the CMLH, writing research publications, and supporting Fellows in their nominations for awards. In addition, the CMLH establishes ongoing connections with the Fellows as they potentially pursue careers and academic achievements in digital healthcare.
Examples of a few of the exciting achievements of the Fellowships program include:
- Devices and techniques for non-invasive intracranial pressure monitoring. This research allows for quantification of traumatic brain injuries and brain swelling and may offer alternatives to the current standard procedure for measurement which is an invasive catheter placed into the ventricle of the brain. This line of work also supports the CMLH project “Non-Invasive Intracranial Pressure Monitoring” led by Dr. Jana Kainerstorfer.
- Precision oncology research to subtype lung cancers from histopathology images using contextual deep learning. This work may help to design individualized treatment protocols for cancer patients.
- Creating 3D printed brain-computer interfaces to be used for applications such as neuroprosthetics. This approach leverages the capabilities of aerosol jet-printing to customize electrode placement of the brain-computer interfaces as well as increase the recording site density.
- Intersections of digital fabrication, healthcare, and disability justice. This research develops new generative design frameworks that support makers in healthcare settings and has contributed to the burgeoning field of algorithmic machine knitting.
“The CMLH program gave a unique opportunity to explore how my research on generative design could directly impact healthcare practices. Since completing my fellowship, my research has had a significant impact on the field. This is built on the support of CMLH and my talented cohort.” – Megan Hofmann, PhD student in CMU HCII.
“The CMLH digital health-fellowship program provided me with the opportunity to take on a high-risk project that ultimately succeeded and became my PhD thesis. During my fellowship, I developed and deployed a mobile health intervention app for sleep that adapts sleep recommendations to the user, automatically using artificial intelligence. The app uses sleep data from a wearable and user feedback to estimate which recommendations are best and are preferred by the user.” – Julian Ramos, PhD student in CMU HCII.