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Project-Based Learning

Hopkins BME offers a variety of project-based courses. Under the guidance of our faculty experts, students work in teams to solve health-related challenges associated with their focus area.

Precision Care Medicine

Students apply machine learning and mechanistic and statistical modeling to develop data-driven solutions to healthcare problems that arise in anesthesiology and critical care medicine, including determining when patients should be admitted to or discharged from intensive care units, predicting changes in the state of patient health, and selecting optimal patient therapies. Teams work with faculty from the Johns Hopkins Institute for Computational Medicine and the departments of Anesthesiology & Critical Care Medicine, Neurology, and Psychiatry & Behavioral Sciences to design, validate, and deploy applications that deliver computational methods to address underlying healthcare problems.

Introduction to Rehabilitation Engineering

Students work in teams to develop new and improved needs-based devices to be used for measurement or treatment of an impairment or disability. In doing so, students learn the biomedical engineering design process and its application to those with disabilities.

Independent Design

Students work to design and evaluate a system that demonstrates creative thinking and experimental skills, and draws upon advanced topics of biomedical and traditional engineering.

Advanced Design

This course is the follow-up to our undergraduate Design Team course sequence. It provides project-specific mentorship and guidance for a team of students to complete a sophisticated prototype and demonstrate technical feasibility towards impacting a clinical problem. Allowing projects to continue as part of the curriculum beyond the first year of Design Team provides support for more advanced testing, de-risking, funding applications, and translation.

NeuroData Design

Students work in teams to build machine learning and statistical tools to answer neuroscientific questions. Working closely with neuroscientists, software developers, and data scientists, students develop open source algorithms and software. Teams work on applying their tools to real data, and submit manuscript drafts for future publication.

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